#836 by GitHub stars
liangdabiao/amazon-sorftime-research-MCP-skill
亚马逊选品 之 Listing全维度穿透分析报告 加上 全品类分析 ,关键词分析,差评分析 ,市场调研 等等。codex/claude code agent skill, amazon sorftime MCP/西柚mcp/sif mcp/卖家精灵sellersprite 智能体skill. 亚马逊跨境电商skill工具集。
History
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Verified commit 99c65df845e3f63f17865122fb5ea3076304e849
git clone --filter=blob:none --no-checkout https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill.git .hotskills/liangdabiao-amazon-sorftime-research-mcp-skill && git -C .hotskills/liangdabiao-amazon-sorftime-research-mcp-skill checkout --detach 99c65df845e3f63f17865122fb5ea3076304e849
# Copy each selected skill directory from .hotskills/liangdabiao-amazon-sorftime-research-mcp-skill into .claude/skills/<skill-name>/Heat
7.2- Star growth, last 7 daysAhead of 94% of tracked repositories
- Star growth, last 24 hoursAhead of 86% of tracked repositories
- Rank movement, last 7 daysAhead of 69% of tracked repositories
- Commits, last 30 daysAhead of 64% of tracked repositories
- Accounts asking about it through MCP, last 7 daysNot available
- Hot votes this weekAhead of 0% of tracked repositories
Heat never changes the order by stars, and sponsorship never touches it. How heat works
Stars over time
Individual skills in this repository
- amazon-analyse
SKILLS/skills/amazon-analyse - amazon-listing-builder
SKILLS/skills/amazon-listing-builder - category-selection
SKILLS/skills/category-selection - keyword-research
SKILLS/skills/keyword-research - product-research
SKILLS/skills/product-research - review-analysis
SKILLS/skills/review-analysis - sellersprite-amazon-research
SKILLS/skills/sellersprite-amazon-research - sif-amazon-research
SKILLS/skills/sif-amazon-research - xiyou-insight
SKILLS/skills/xiyou-insight
How it works
amazon-analyse
When your agent uses it
对亚马逊竞品Listing进行全维度穿透分析,包括文案逻辑、评论分析、关键词分析、市场动态等。分析完成后自动保存为Markdown报告文档到reports/目录。Invoke when user uses /amazon-analyse command with a product ASIN.
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
4,607 tokensWhen the skill is activated
Reference documents
8,187 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 快速参考
- 触发条件
- 角色设定
- 数据来源
- 分析流程
- 参考文档
- 参考资料
Files
README.mddoc5,981 bytesSKILL.mdcore15,700 bytesSKILL.mdcore15,700 bytesSKILL.mdcore15,700 bytesSKILL.mdcore15,700 bytesSKILL.mdcore15,700 bytesreferences/api-tools-reference.mddoc4,828 bytesreferences/report-management.mddoc2,271 bytesreferences/sorftime-mcp-api.mddoc13,659 bytesreferences/sorftime_mcp文档.txtdoc12,765 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubamazon-listing-builder
When your agent uses it
亚马逊爆款 Listing 打造助手(基于 Cosmo 语义算法 + Alexa/Rufus 对话式购物趋势)。通过"先分析、再生成、最后校验"的 AI 工程化流程,把 Listing 从"关键词堆砌"升级为"语义覆盖 + 需求证据 + 答案型内容"。提供八步工作流(关键词分层词库 → 用户问题库 → 卖点证据库 → 标题 → 五点 → 描述A+ → Search Terms → QA)、给 Codex 的可复用提示词、真实案例(抗 UV 户外仿真植物、down filled pillows QA)以及五大常见误区检查。触发场景:(1) 用户说"帮我写 Listing / 写标题 / 写五点 / 写描述 / 写 A+ / 写 QA / 写 Search Terms"(2) 用户输入 /listing-builder, /build-listing, /cosmo-listing, /alexa-qa, /listing-title, /listing-bullets, /listing-aplus, /listing-st, /listing-qa(3) 用户提及 Cosmo 算法、Alexa 算法、Rufus、对话式购物、语义搜索、答案型 Listing(4) 用户希望结合卖家精灵 MCP 数据做关键词分层与痛点映射。适用于亚马逊美国站等站点的运营、Listing 优化师、产品开发、跨境营销人员。
What it loads into context
Frontmatter
326 tokensAlways available to the agent
SKILL.md
3,425 tokensWhen the skill is activated
Reference documents
46,165 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 🚨 铁律 0:数据来源优先级(必须先读)
- 一、为什么需要这个 Skill
- 二、核心方法论:先分析、再生成、最后校验
- 三、八步工作流总览
- 四、给 Codex / Claude 的主提示词(直接复用)
- 五、子命令
- 六、与卖家精灵 MCP 集成(必须使用,本项目已配置)
- 七、五大常见误区(必须主动检查)
- 八、真实案例参考
- 九、输出格式规范
- 十、执行流程
- 十一、关键原则(每次都要回顾)
Files
README.mddoc17,768 bytesexamples/down-pillows-qa-example.mddoc6,834 bytesexamples/layered-keyword-template.mddoc3,662 bytesexamples/uv-outdoor-plants-fullcase.mddoc11,767 bytesprompts/compliance-check-prompt.mddoc4,290 bytesprompts/data-iteration-prompt.mddoc5,657 bytesprompts/layered-keyword-prompt.mddoc4,228 bytesprompts/master-prompt.mddoc7,021 bytesprompts/multiversion-prompt.mddoc4,287 bytesprompts/painpoint-mapping-prompt.mddoc4,284 bytesprompts/semantic-coverage-prompt.mddoc4,009 bytesreference/common-mistakes.mddoc3,978 bytesreference/cosmo-alexa-algorithm.mddoc5,258 bytesreference/mcp-mandatory-protocol.mddoc9,308 bytesreference/output-format-spec.mddoc6,319 bytesreference/sellersprite-mcp-integration.mddoc6,908 bytesskill.mdcore11,394 bytesworkflow/step-1-keyword-library.mddoc5,896 bytesworkflow/step-2-question-library.mddoc6,328 bytesworkflow/step-3-evidence-library.mddoc6,696 bytesworkflow/step-4-title-design.mddoc6,004 bytesworkflow/step-5-bullet-points.mddoc6,219 bytesworkflow/step-6-description-aplus.mddoc7,011 bytesworkflow/step-7-search-terms.mddoc4,807 bytesworkflow/step-8-qa-design.mddoc8,737 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcategory-selection
When your agent uses it
亚马逊品类自动化选品分析技能。通过五维评分模型对亚马逊品类进行深度市场调研,生成Markdown分析报告。当用户使用 /category-selection 命令或提出'分析XX品类'、'XX品类市场调研'、'XX品类选品'等需求时触发此技能。支持配置分析数量,默认Top20。
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
4,946 tokensWhen the skill is activated
Reference documents
13,864 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 快速参考
- 触发条件
- 角色设定
- 五维评分模型 (标准版)
- 完整分析流程
- 数据处理工具
- HTML 可视化仪表板
- 故障排查
- 支持的站点
- 注意事项
- 参考文档
Scripts executed separately
scripts/analyze_category.pyscripts/data_adapter.pyscripts/data_utils.pyscripts/extract_category_stats.pyscripts/extract_top_products.pyscripts/fix_encoding.pyscripts/generate_excel_report.pyscripts/generate_markdown_report.pyscripts/generate_reports.pyscripts/keywords_parser.pyscripts/keywords_parser_v1_backup.pyscripts/parse_category_report.pyscripts/parse_sorftime_sse.pyscripts/sse_decoder.pyscripts/sse_decoder_v3_backup.pyscripts/trend_parser.pyscripts/workflow.py
Files
CHANGELOG.mddoc13,217 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesSKILL.mdcore16,365 bytesassets/dashboard_template.htmlasset20,070 bytesassets/report_template.mddoc3,032 bytesreferences/api-quick-reference.mddoc2,704 bytesreferences/category-api-reference.mddoc5,762 bytesreferences/scoring-standard.mddoc6,225 bytesreferences/sorftime-mcp-api.mddoc13,717 bytesscripts/analyze_category.pyruns16,143 bytesscripts/data_adapter.pyruns13,286 bytesscripts/data_utils.pyruns18,205 bytesscripts/extract_category_stats.pyruns5,827 bytesscripts/extract_top_products.pyruns6,187 bytesscripts/fix_encoding.pyruns3,206 bytesscripts/generate_excel_report.pyruns20,109 bytesscripts/generate_markdown_report.pyruns26,439 bytesscripts/generate_reports.pyruns46,281 bytesscripts/keywords_parser.pyruns8,646 bytesscripts/keywords_parser_v1_backup.pyruns9,566 bytesscripts/parse_category_report.pyruns11,322 bytesscripts/parse_sorftime_sse.pyruns12,093 bytesscripts/sse_decoder.pyruns18,846 bytesscripts/sse_decoder_v3_backup.pyruns13,221 bytesscripts/trend_parser.pyruns7,327 bytesscripts/workflow.pyruns34,350 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubkeyword-research
When your agent uses it
亚马逊关键词深度调研与智能分类分析。基于 Sorftime MCP 数据采集 2000+ 关键词,通过 LLM Agent 按 8 维度智能分类(否定词、品牌词、材质词、场景词、属性词、功能词、核心词、其他),生成 Markdown 报告、CSV 词库和 HTML 仪表板。触发方式:/keyword-research {ASIN} {SITE}
What it loads into context
Frontmatter
109 tokensAlways available to the agent
SKILL.md
4,160 tokensWhen the skill is activated
Reference documents
7,465 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 快速参考
- 触发条件
- 角色设定
- 数据采集策略:方案 A(基于 ASIN 的深度分析)
- 关键词分类:8 维智能分类模型
- 执行流程
- 产品信息支持(可选)
- Sorftime API 参考
- 支持的站点
- 注意事项
- 故障排查
- 参考文档
- 手动 LLM 分类流程
- 版本更新记录
Scripts executed separately
scripts/csv_generator.pyscripts/data_parser.pyscripts/generate_html_dashboard.pyscripts/generate_markdown_report.pyscripts/keyword_collector.pyscripts/regen_md_html.pyscripts/regenerate_reports.pyscripts/test_html_gen.pyscripts/test_load_classify.pyscripts/workflow.py
Files
README.mddoc3,974 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesSKILL.mdcore15,522 bytesreferences/api-tools-reference.mddoc4,828 bytesreferences/report-management.mddoc2,271 bytesreferences/sorftime-mcp-api.mddoc13,659 bytesreferences/sorftime_mcp文档.txtdoc12,765 bytesscripts/csv_generator.pyruns8,744 bytesscripts/data_parser.pyruns9,191 bytesscripts/generate_html_dashboard.pyruns23,509 bytesscripts/generate_markdown_report.pyruns12,610 bytesscripts/keyword_collector.pyruns24,092 bytesscripts/regen_md_html.pyruns2,146 bytesscripts/regenerate_reports.pyruns9,998 bytesscripts/test_html_gen.pyruns784 bytesscripts/test_load_classify.pyruns1,014 bytesscripts/workflow.pyruns32,082 bytestemplates/dashboard_template.htmlasset13,912 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubproduct-research
When your agent uses it
基于Sorftime MCP的深度选品调研。通过LLM Agent执行多维度分析:数据采集→属性标注→交叉分析→竞品VOC→壁垒评估→选品决策评估。交互式执行,输出Markdown报告和Dashboard看板。
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
6,525 tokensWhen the skill is activated
Reference documents
12,777 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 定位
- Script Directory
- 执行流程(两阶段)
- 执行流程(交互式)
- Dashboard 渲染规范
- LLM Prompt 模板库
- 硬性规则(⛔ 不可省略)
- 常见场景策略
- 与其他 Skills 的关系
- 支持的站点
- 注意事项
- 故障排查
Scripts executed separately
scripts/api_client.pyscripts/collect_data.pyscripts/fix_data_json.pyscripts/get_reviews.pyscripts/render_dashboard.pyscripts/run_analysis.pyscripts/validate_data.pyscripts/verify_reviews.py
Files
README.mddoc1,979 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesSKILL.mdcore21,364 bytesreferences/api-quick-reference.mddoc2,704 bytesreferences/api-reference.mddoc5,634 bytesreferences/prompt_templates.mddoc11,987 bytesreferences/sorftime-mcp-api.mddoc13,717 bytesreferences/troubleshooting.mddoc5,295 bytesscripts/api_client.pyruns25,155 bytesscripts/collect_data.pyruns20,499 bytesscripts/fix_data_json.pyruns4,796 bytesscripts/get_reviews.pyruns4,549 bytesscripts/render_dashboard.pyruns28,552 bytesscripts/run_analysis.pyruns21,426 bytesscripts/validate_data.pyruns8,155 bytesscripts/verify_reviews.pyruns2,735 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubreview-analysis
When your agent uses it
对亚马逊商品评论进行深度分析,自动识别产品痛点、分析退货原因,生成改进建议和客服回复模板。Invoke when user uses /review-analysis command with a product ASIN.
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
4,938 tokensWhen the skill is activated
Reference documents
7,758 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 快速参考
- 报告输出结构
- 触发条件
- 角色设定
- 分析流程(优化版 v7.0 - 6维分析框架)
- 分析框架
- 报告模板
- 亚马逊合规要求
- 支持的站点
- 故障排查
- 最佳实践
Files
SKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesSKILL.mdcore16,786 bytesassets/email_templates/quality_issue.mddoc10,201 bytesreferences/painpoint_taxonomy.mddoc5,437 bytes设计文档.mddoc14,609 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsellersprite-amazon-research
When your agent uses it
卖家精灵 Amazon 全链路数据调研 Skill。通过 43 个 MCP 数据工具完成选品分析、关键词研究、竞品监控、市场分析、定价策略、评论分析、广告优化、流量分析、Listing 优化和蓝海机会挖掘。触发场景:(1) 用户询问 Amazon 选品/市场/竞品分析 (2) 用户输入 /product-research, /market-analysis, /competitor-analysis, /keyword-research, /listing-optimizer, /traffic-analysis, /opportunity-finder, /review-insights, /pricing-strategy, /ad-optimizer 等命令 (3) 用户提及新品爆发、隐形爆款、ABA 增长词、低品牌垄断、评论分析等选品策略。适用于跨境电商卖家、Amazon 运营和产品开发决策。
What it loads into context
Frontmatter
202 tokensAlways available to the agent
SKILL.md
7,813 tokensWhen the skill is activated
Reference documents
15,097 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 重要:MCP 连接配置
- 工具调用方式
- 关键:参数传递模式
- 全局参数默认值
- 字段映射与刻度陷阱(重要)
- MCP 响应解析要点
- 一、综合分析工作流
- 二、战术选品策略卡
- 三、MCP 工具参考
- 四、输出格式(必读:必须保存为文件)
- 五、推荐组合链路
- 六、实操技巧(实测经验)
- 七、实测经验与参数陷阱
- 八、报告质量检查清单
Scripts executed separately
scripts/competitor_analysis.pyscripts/dji_pocket3_analysis.pyscripts/fix_keyword_report.pyscripts/keyword_deep_analysis.pyscripts/keyword_research.pyscripts/lavalier_analysis.pyscripts/mcp_call.pyscripts/review_analysis.pyscripts/tactical_strategies.py
Files
README.mddoc9,558 bytescomprehensive/ad-optimizer.mddoc1,255 bytescomprehensive/competitor-analysis.mddoc1,996 bytescomprehensive/keyword-research.mddoc1,602 bytescomprehensive/listing-optimizer.mddoc1,265 bytescomprehensive/market-analysis.mddoc3,761 bytescomprehensive/opportunity-finder.mddoc1,169 bytescomprehensive/pricing-strategy.mddoc1,157 bytescomprehensive/product-research.mddoc1,693 bytescomprehensive/review-insights.mddoc1,112 bytescomprehensive/traffic-analysis.mddoc1,421 bytesreference/asin_detail.mddoc1,232 bytesreference/competitor_lookup.mddoc1,173 bytesreference/keyword_miner.mddoc2,153 bytesreference/market_research.mddoc4,990 bytesreference/product_research.mddoc2,145 bytesreference/tools_index.mddoc4,764 bytesreference/traffic_keyword.mddoc1,889 bytesscripts/competitor_analysis.pyruns13,493 bytesscripts/dji_pocket3_analysis.pyruns12,558 bytesscripts/fix_keyword_report.pyruns6,743 bytesscripts/keyword_deep_analysis.pyruns20,990 bytesscripts/keyword_research.pyruns8,449 bytesscripts/lavalier_analysis.pyruns19,110 bytesscripts/mcp_call.pyruns1,229 bytesscripts/review_analysis.pyruns9,096 bytesscripts/tactical_strategies.pyruns11,987 bytesskill.mdcore25,610 bytesskill.mdcore25,610 bytesskill.mdcore25,610 bytesskill.mdcore25,610 bytesskill.mdcore25,610 bytesskill.mdcore25,610 bytesskill.mdcore25,610 bytestactical/aba-high-growth-trend.mddoc553 bytestactical/fbm-intercept.mddoc268 bytestactical/hidden-bestseller.mddoc353 bytestactical/high-margin-lightweight.mddoc278 bytestactical/high-new-product-ratio.mddoc348 bytestactical/high-ticket-long-tail.mddoc357 bytestactical/hot-low-rating.mddoc366 bytestactical/local-premium-disruption.mddoc310 bytestactical/low-brand-monopoly.mddoc356 bytestactical/low-monopoly-keyword.mddoc392 bytestactical/natural-traffic-audit.mddoc340 bytestactical/new-product-burst.mddoc527 bytestactical/poor-listing-winner.mddoc295 bytestactical/review-sentiment.mddoc485 bytestactical/seasonal-prepositioning.mddoc451 bytestactical/title-density-gap.mddoc350 bytestactical/variant-gap-analysis.mddoc367 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsif-amazon-research
When your agent uses it
Use this skill for Amazon e-commerce research, market validation, competitor analysis, traffic diagnosis, keyword strategy, advertising review, launch evaluation, and growth optimization using the Sif MCP server and Sif's real marketplace, traffic, keyword, sales, and ad data. Trigger when users mention Sif, Sif MCP, ASIN research, Amazon product opportunity research, keyword opportunity, competitor teardown, traffic drop/root-cause diagnosis, advertising structure review, or whether a product/market is worth entering, launching, scaling, optimizing, or abandoning.
What it loads into context
Frontmatter
119 tokensAlways available to the agent
SKILL.md
864 tokensWhen the skill is activated
Reference documents
3,259 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Operating rules
- Core workflow
- Required output format
- Guardrails
Files
SKILL.mdcore4,095 bytesSKILL.mdcore4,095 bytesreferences/field-notes.mddoc4,347 bytesreferences/research-playbooks.mddoc5,550 bytesreferences/sif-tool-map.mddoc4,328 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubxiyou-insight
When your agent uses it
基于西柚洞察MCP的亚马逊竞品分析与广告策略工具。提供7大核心工作场景:实时监控广告投放效果、快速找到高性价比流量缺口、快速拆解对标竞对打法、提升新品推广效率、精准拆解竞品流量以及广告策略、透视竞品广告策略和预算、高效搭建关键词库。适用于亚马逊卖家进行竞品分析、广告优化和关键词研究。
What it loads into context
Frontmatter
140 tokensAlways available to the agent
SKILL.md
3,997 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 定位
- MCP 工具速查表
- 7大核心工作场景
- Script Directory
- 执行流程
- 数据字段命名规范
- 支持的站点
- 注意事项
- 与其他Skills的关系
Scripts executed separately
scripts/dashboard_generator.pyscripts/data_aggregator.pyscripts/report_generator.pyscripts/scenarios/__init__.pyscripts/scenarios/ad_budget.pyscripts/scenarios/ad_monitoring.pyscripts/scenarios/base.pyscripts/scenarios/competitor_analysis.pyscripts/scenarios/keyword_database.pyscripts/scenarios/new_product.pyscripts/scenarios/traffic_gap.pyscripts/workflow.pyscripts/workflow_competitor_analysis.py
Files
SKILL.mdcore13,630 bytesscripts/dashboard_generator.pyruns14,761 bytesscripts/data_aggregator.pyruns12,680 bytesscripts/report_generator.pyruns19,317 bytesscripts/scenarios/__init__.pyruns872 bytesscripts/scenarios/ad_budget.pyruns13,235 bytesscripts/scenarios/ad_monitoring.pyruns9,469 bytesscripts/scenarios/base.pyruns2,268 bytesscripts/scenarios/competitor_analysis.pyruns15,550 bytesscripts/scenarios/keyword_database.pyruns13,301 bytesscripts/scenarios/new_product.pyruns11,689 bytesscripts/scenarios/traffic_gap.pyruns9,825 bytesscripts/workflow.pyruns16,231 bytesscripts/workflow_competitor_analysis.pyruns13,461 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubSkills included
- amazon-analyse
- amazon-listing-builder
- category-selection
- keyword-research
- product-research
- review-analysis
- sellersprite-amazon-research
- sif-amazon-research
- xiyou-insight
Repository facts
- License
- No license detected
- Created
- Mar 2, 2026
- Last pushed
- Oct 28, 2026
- Forks
- 155
- Open issues
- 9
- Project activity
- Active
Rank over the last 12 weeks
Now #836 · best #672 · down 70 in 30 days
- #833 on Nov 1
- #835 on Nov 2
- #836 from Nov 3 to Nov 4
- #834 on Nov 5
- #832 on Nov 6
- #836 since Nov 7
81 earlier periods
- #711 on Aug 2
- #692 on Aug 8
- #696 on Aug 9
- #723 on Aug 10
- #729 on Aug 11
- #726 on Aug 12
- #723 on Aug 13
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- #675 on Sep 19
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- #672 from Sep 25 to Sep 26
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- #729 on Oct 9
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- #713 on Oct 11
- #727 on Oct 12
- #733 on Oct 13
- #744 on Oct 14
- #735 on Oct 15
- #739 on Oct 16
- #713 from Oct 17 to Oct 18
- #750 from Oct 19 to Oct 20
- #756 on Oct 21
- #733 on Oct 22
- #739 on Oct 23
- #705 on Oct 24
- #833 on Oct 25
- #833 on Oct 28
- #830 on Oct 29
- #833 on Oct 30
- #834 on Oct 31
Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 3, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 79 notes
SKILLS/skills/amazon-analyse/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/amazon-analyse/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/amazon-analyse/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/amazon-analyse/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILLS/skills/category-selection/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- 335 network referencesin 49 files: amazon-analyse/references/api-tools-reference.md:1 keyword-research/references/api-tools-reference.md:1 amazon-listing-builder/reference/sellersprite-mcp-integration.md:12 and 46 more
- No hidden or obfuscated text
- No instruction overrides
- 57 executable scriptsin 57 files: category-selection/scripts/analyze_category.py:1 category-selection/scripts/data_adapter.py:1 category-selection/scripts/data_utils.py:1 and 54 more
- 102 references to secretsin 20 files: category-selection/scripts/workflow.py:44 product-research/scripts/api_client.py:58 category-selection/SKILL.md:40 and 17 more
- No requests to vote in Hot
Show all 494 signals by file
SKILLS/skills/amazon-analyse/README.md
- Network accessline 141
[Credential-related source omitted] - Access to secretsline 141
[Credential-related source omitted] - Network accessline 157
"sorftime": { "type": "streamableHttp", "url": "https://mcp.sorftime.com?key=YOUR_API_KEY", - Network accessline 158
"type": "streamableHttp", "url": "https://mcp.sorftime.com?key=YOUR_API_KEY", "name": "Sorftime MCP", - Network accessline 159
[Credential-related source omitted] - Access to secretsline 159
[Credential-related source omitted] - Network accessline 169
1. 访问 [Sorftime官网](https://www.sorftime.com) - Network accessline 210
1. 检查网络连接 2. 验证API Key是否有效 3. 增加超时时间:`curl --max-time 30` - Network accessline 212
3. 增加超时时间:`curl --max-time 30` - Network accessline 276
- [Sorftime官网](https://www.sorftime.com) - Network accessline 277
- [Amazon MWS文档](https://developer.amazonservices.com/) - Network accessline 278
- [Claude Code文档](https://claude.com/claude-code) - Network accessline 279
- [参考公众号](https://mp.weixin.qq.com/s/agrml8THPvCmMxOMMmxKzA)
SKILLS/skills/amazon-analyse/SKILL.md
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[Credential-related source omitted] - Access to secretsline 23
[Credential-related source omitted] - Network accessline 52
**重要提示**: - 所有数据需通过 curl POST 请求获取 - Network accessline 53
- 所有数据需通过 curl POST 请求获取 - Network accessline 67
# 验证 ASIN 是否存在 curl -s -X POST "https://mcp.sorftime.com?key=YOUR_API_KEY" \ - Network accessline 68
[Credential-related source omitted] - Access to secretsline 68
[Credential-related source omitted] - Network accessline 80
Sorftime MCP 使用 **Server-Sent Events (SSE)** 协议,需要通过 curl POST 请求调用。 - Network accessline 84
[Credential-related source omitted] - Access to secretsline 84
[Credential-related source omitted] - Network accessline 312
- [API 工具参考](references/api-tools-reference.md) - 完整的 curl 调用格式和故障排查
SKILLS/skills/amazon-analyse/references/api-tools-reference.md
- Network accessline 1
# Sorftime MCP 工具参考 (curl 调用格式) - Network accessline 6
[Credential-related source omitted] - Access to secretsline 6
[Credential-related source omitted] - Network accessline 17
[Credential-related source omitted] - Access to secretsline 17
[Credential-related source omitted] - Network accessline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Network accessline 31
[Credential-related source omitted] - Access to secretsline 31
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[Credential-related source omitted] - Access to secretsline 39
[Credential-related source omitted] - Network accessline 46
[Credential-related source omitted] - Access to secretsline 46
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[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Network accessline 61
[Credential-related source omitted] - Access to secretsline 61
[Credential-related source omitted] - Network accessline 73
# 并发获取所有数据(使用不同的 id) curl ... '{"id":1,...}' & - Network accessline 74
curl ... '{"id":1,...}' & - Network accessline 75
curl ... '{"id":2,...}' & - Network accessline 76
curl ... '{"id":3,...}' & - Network accessline 77
curl ... '{"id":4,...}' & - Network accessline 78
curl ... '{"id":5,...}' & - Network accessline 79
curl ... '{"id":6,...}' & - Network accessline 85
(curl ... '{"id":1,...}' && curl ... '{"id":2,...}' && ...) - Network accessline 105
[Credential-related source omitted] - Access to secretsline 105
[Credential-related source omitted] - Network accessline 138
**现象**:curl 请求超时或无响应 - Network accessline 141
1. 检查网络连接 2. 验证 API Key 是否有效 3. 检查 Sorftime 服务状态:`curl -I https://mcp.sorftime.com` - Network accessline 142
2. 验证 API Key 是否有效 3. 检查 Sorftime 服务状态:`curl -I https://mcp.sorftime.com` 4. 增加超时时间:`curl --max-time 30` - Network accessline 143
3. 检查 Sorftime 服务状态:`curl -I https://mcp.sorftime.com` - Network accessline 144
4. 增加超时时间:`curl --max-time 30`
SKILLS/skills/amazon-analyse/references/sorftime-mcp-api.md
SKILLS/skills/amazon-listing-builder/README.md
SKILLS/skills/amazon-listing-builder/reference/mcp-mandatory-protocol.md
- Network accessline 106
// 1. 竞品 QA 板块(MCP 无 QA 工具) mcp__web_reader__webReader({ url: "https://www.amazon.com/ask-questions/B0XXXXXXX", - Network accessline 107
mcp__web_reader__webReader({ url: "https://www.amazon.com/ask-questions/B0XXXXXXX", return_format: "text", - Network accessline 108
url: "https://www.amazon.com/ask-questions/B0XXXXXXX", - Network accessline 113
// 2. Reddit / TikTok 站外买家反馈 mcp__web_reader__webReader({ url: "https://www.reddit.com/r/.../...", - Network accessline 114
mcp__web_reader__webReader({ url: "https://www.reddit.com/r/.../...", return_format: "text" - Network accessline 115
url: "https://www.reddit.com/r/.../...", - Network accessline 119
// ❌ 错误示例:抓 Amazon 评论页 // mcp__web_reader__webReader({ // url: "https://www.amazon.com/product-reviews/B07PQFT83F?filterByStar=critical" - Network accessline 120
// mcp__web_reader__webReader({ // url: "https://www.amazon.com/product-reviews/B07PQFT83F?filterByStar=critical" // }) - Network accessline 121
// url: "https://www.amazon.com/product-reviews/B07PQFT83F?filterByStar=critical"
SKILLS/skills/amazon-listing-builder/reference/sellersprite-mcp-integration.md
- Network accessline 12
"mcpServers": { "sellersprite": { "url": "https://mcp.sellersprite.com/mcp", - Network accessline 13
"sellersprite": { "url": "https://mcp.sellersprite.com/mcp", "headers": { - Network accessline 14
"url": "https://mcp.sellersprite.com/mcp", - Network accessline 23
**关键**: - URL 必须是 `https://mcp.sellersprite.com/mcp`(不是 `/sse`) - Network accessline 24
- URL 必须是 `https://mcp.sellersprite.com/mcp`(不是 `/sse`) - Network accessline 36
curl -s -X POST "https://mcp.sellersprite.com/mcp" \ - Network accessline 48
"params":{"name":"keyword_miner","arguments":{"request":{ "marketplace":"US","keyword":"artificial flowers"}}}}}).encode() req = urllib.request.Request("https://mcp.sellersprite.com/mcp", - Network accessline 49
"marketplace":"US","keyword":"artificial flowers"}}}}}).encode() req = urllib.request.Request("https://mcp.sellersprite.com/mcp", data=payload, - Network accessline 50
req = urllib.request.Request("https://mcp.sellersprite.com/mcp", - Network accessline 53
"Accept":"application/json, text/event-stream", "secret-key":"<KEY>"}) with urllib.request.urlopen(req) as resp: - Network accessline 54
"secret-key":"<KEY>"}) with urllib.request.urlopen(req) as resp: data = json.loads(resp.read().decode('utf-8')) - Network accessline 55
with urllib.request.urlopen(req) as resp: - Network accessline 151
payload = json.dumps({"jsonrpc":"2.0","id":1,"method":"tools/call", "params":{"name":tool,"arguments":args}}).encode() req = urllib.request.Request("https://mcp.sellersprite.com/mcp", - Network accessline 152
"params":{"name":tool,"arguments":args}}).encode() req = urllib.request.Request("https://mcp.sellersprite.com/mcp", data=payload, - Network accessline 153
req = urllib.request.Request("https://mcp.sellersprite.com/mcp", - Network accessline 156
"Accept":"application/json, text/event-stream", "secret-key":"<YOUR_KEY>"}) with urllib.request.urlopen(req) as resp: - Network accessline 157
"secret-key":"<YOUR_KEY>"}) with urllib.request.urlopen(req) as resp: return json.loads(json.loads(resp.read())['result']['content'][0]['text']) - Network accessline 158
with urllib.request.urlopen(req) as resp:
SKILLS/skills/amazon-listing-builder/workflow/step-1-keyword-library.md
- Network accessline 38
// 错误:用浏览器抓 Amazon 搜词建议 mcp__web_reader__webReader({url:"https://www.amazon.com/s?k=artificial+flowers"}) - Network accessline 39
mcp__web_reader__webReader({url:"https://www.amazon.com/s?k=artificial+flowers"}) - Network accessline 41
mcp__web_reader__webReader({url:"https://www.amazon.com/s?k=..."})
SKILLS/skills/amazon-listing-builder/workflow/step-2-question-library.md
- Network accessline 35
// 错误:用浏览器抓 Amazon 评论页 mcp__web_reader__webReader({ url:"https://www.amazon.com/product-reviews/B07PQFT83F?filterByStar=critical&pageNumber=1" - Network accessline 36
mcp__web_reader__webReader({ url:"https://www.amazon.com/product-reviews/B07PQFT83F?filterByStar=critical&pageNumber=1" }) - Network accessline 37
url:"https://www.amazon.com/product-reviews/B07PQFT83F?filterByStar=critical&pageNumber=1" - Network accessline 38
}) // 错误:用浏览器抓商品详情页 mcp__web_reader__webReader({url:"https://www.amazon.com/dp/B07XXX..."}) - Network accessline 40
mcp__web_reader__webReader({url:"https://www.amazon.com/dp/B07XXX..."}) - Network accessline 46
// 1. 竞品 QA 板块(MCP 无 QA 工具) mcp__web_reader__webReader({ url:"https://www.amazon.com/ask-questions/B07XXX...", - Network accessline 47
mcp__web_reader__webReader({ url:"https://www.amazon.com/ask-questions/B07XXX...", return_format:"text", - Network accessline 48
url:"https://www.amazon.com/ask-questions/B07XXX...", - Network accessline 53
// 2. 站外买家真实反馈 mcp__web_reader__webReader({url:"https://www.reddit.com/r/..."}) - Network accessline 54
mcp__web_reader__webReader({url:"https://www.reddit.com/r/..."}) - Network accessline 55
mcp__web_reader__webReader({url:"https://www.tiktok.com/..."})
SKILLS/skills/amazon-listing-builder/workflow/step-3-evidence-library.md
- Network accessline 28
// 1. 认证机构官网(验证 CPSIA / FDA / RoHS 等证书真实性) mcp__web_reader__webReader({url:"https://www.fda.gov/..."}) - Network accessline 29
mcp__web_reader__webReader({url:"https://www.fda.gov/..."}) - Network accessline 30
mcp__web_reader__webReader({url:"https://www.cpsc.gov/..."}) - Network accessline 32
// 2. 品牌官网(拿品牌定位语言) mcp__web_reader__webReader({url:"https://brand.com/about"}) - Network accessline 33
mcp__web_reader__webReader({url:"https://brand.com/about"})
SKILLS/skills/amazon-listing-builder/workflow/step-4-title-design.md
SKILLS/skills/amazon-listing-builder/workflow/step-6-description-aplus.md
- Network accessline 12
// 1. 品牌官网(拿品牌定位语言、品牌故事) mcp__web_reader__webReader({url:"https://yourbrand.com/about"}) - Network accessline 13
mcp__web_reader__webReader({url:"https://yourbrand.com/about"}) - Network accessline 14
mcp__web_reader__webReader({url:"https://yourbrand.com/story"}) - Network accessline 16
// 2. 竞品 A+ 模块(如需结构参考,可选) mcp__web_reader__webReader({ url:"https://www.amazon.com/dp/B07XXX...", // 仅看 A+ 模块结构 - Network accessline 17
mcp__web_reader__webReader({ url:"https://www.amazon.com/dp/B07XXX...", // 仅看 A+ 模块结构 retain_images:false - Network accessline 18
url:"https://www.amazon.com/dp/B07XXX...", // 仅看 A+ 模块结构
SKILLS/skills/amazon-listing-builder/workflow/step-8-qa-design.md
- Network accessline 12
// 1. 竞品 QA 板块(补充 MCP 拿不到的问题) mcp__web_reader__webReader({ url:"https://www.amazon.com/ask-questions/B07XXX...", - Network accessline 13
mcp__web_reader__webReader({ url:"https://www.amazon.com/ask-questions/B07XXX...", return_format:"text", - Network accessline 14
url:"https://www.amazon.com/ask-questions/B07XXX...", - Network accessline 19
// 2. Reddit 真实买家提问(可选) mcp__web_reader__webReader({url:"https://www.reddit.com/r/..."}) - Network accessline 20
mcp__web_reader__webReader({url:"https://www.reddit.com/r/..."})
SKILLS/skills/category-selection/CHANGELOG.md
- Access to secretsline 12
[Credential-related source omitted] - Access to secretsline 15
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 23
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 25
[Credential-related source omitted] - Network accessline 359
Claude Code ↓ MCP 工具调用 (curl via Bash) - Network accessline 360
↓ MCP 工具调用 (curl via Bash) ↓ - Network accessline 361
MCP 工具调用 (curl via Bash) - Network accessline 389
| 章节 | v3.x | v4.0 | |------|------|------| | MCP 调用 | 描述 Python 脚本 | 描述 curl 调用 MCP | - Network accessline 390
|------|------|------| | MCP 调用 | 描述 Python 脚本 | 描述 curl 调用 MCP | | 数据解析 | 导入 Python 模块 | Claude Code 直接处理 | - Network accessline 391
| MCP 调用 | 描述 Python 脚本 | 描述 curl 调用 MCP | - Network accessline 392
| 数据解析 | 导入 Python 模块 | Claude Code 直接处理 | | 工具参考 | 混合描述 | 统一 curl 格式 | | 报告生成 | Python 脚本 | Write 工具 | - Network accessline 393
| 工具参考 | 混合描述 | 统一 curl 格式 |
SKILLS/skills/category-selection/SKILL.md
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# 并发获取 Top3 产品详情 curl ... '{"id":3,"method":"tools/call","params":{"name":"product_detail","arguments":{"amzSite":"US","asin":"ASIN1"}}}' & - Network accessline 137
curl ... '{"id":3,"method":"tools/call","params":{"name":"product_detail","arguments":{"amzSite":"US","asin":"ASIN1"}}}' & - Network accessline 138
curl ... '{"id":4,"method":"tools/call","params":{"name":"product_detail","arguments":{"amzSite":"US","asin":"ASIN2"}}}' & - Network accessline 139
curl ... '{"id":5,"method":"tools/call","params":{"name":"product_detail","arguments":{"amzSite":"US","asin":"ASIN3"}}}' & - Network accessline 146
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"mcpServers": { "sorftime": { "url": "https://mcp.sorftime.com?key=YOUR_API_KEY" - Network accessline 328
"sorftime": { "url": "https://mcp.sorftime.com?key=YOUR_API_KEY" } - Network accessline 329
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# 先用大类目搜索,查看返回的子类目列表 curl -s -X POST "https://mcp.sorftime.com?key={API_KEY}" \ - Network accessline 378
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curl -s -X POST "https://mcp.sorftime.com?key={YOUR_KEY}" \ - Access to secretsline 465
[Credential-related source omitted]
SKILLS/skills/category-selection/assets/dashboard_template.html
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<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>{{CATEGORY_NAME}} 品类市场调研报告</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script> - Network accessline 6
<title>{{CATEGORY_NAME}} 品类市场调研报告</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script> <style> - Network accessline 7
<script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
SKILLS/skills/category-selection/references/api-quick-reference.md
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SKILLS/skills/category-selection/references/category-api-reference.md
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# 并发调用11个趋势接口 curl -s -X POST "https://mcp.sorftime.com?key=YOUR_API_KEY" \ - Network accessline 52
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# 需要对100个ASIN逐个调用 curl -s -X POST "https://mcp.sorftime.com?key=YOUR_API_KEY" \ - Network accessline 98
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SKILLS/skills/category-selection/references/sorftime-mcp-api.md
SKILLS/skills/category-selection/scripts/analyze_category.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 22
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self.base_url = "https://mcp.sorftime.com" - Access to secretsline 48
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try: response = requests.post( - Network accessline 60
response = requests.post(
SKILLS/skills/category-selection/scripts/data_adapter.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/data_utils.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/extract_category_stats.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/extract_top_products.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/fix_encoding.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/generate_excel_report.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/generate_markdown_report.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/generate_reports.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/keywords_parser.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/keywords_parser_v1_backup.py
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#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/parse_category_report.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/parse_sorftime_sse.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/sse_decoder.py
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#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/sse_decoder_v3_backup.py
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#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/trend_parser.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/category-selection/scripts/workflow.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 44
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# 从 URL 中提取 API key: https://mcp.sorftime.com?key=XXX - Access to secretsline 67
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rating = safe_float(p.get('星级', 0)) asin = p.get('ASIN', 'N/A') report += f"| {i} | [{asin}](https://www.amazon.com/dp/{asin}) | {title} | ${price:.2f} | {sales:,} | ${revenue:,.2f} | {reviews:,} | {rating:.1f} | {p.get('品牌' - Network accessline 547
report += f"| {i} | [{asin}](https://www.amazon.com/dp/{asin}) | {title} | ${price:.2f} | {sales:,} | ${revenue:,.2f} | {reviews:,} | {rating:.1f} | {p.get('品牌', 'N/A')} |\n" - Access to secretsline 605
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"""执行 curl 请求,返回解析后的结果""" - Access to secretsline 921
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SKILLS/skills/keyword-research/SKILL.md
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# 首先获取产品详情以获取 NodeID curl -s -X POST "https://mcp.sorftime.com?key={API_KEY}" \ - Network accessline 142
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# 然后获取类目关键词 curl -s -X POST "https://mcp.sorftime.com?key={API_KEY}" \ - Network accessline 147
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SKILLS/skills/keyword-research/references/api-tools-reference.md
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# Sorftime MCP 工具参考 (curl 调用格式) - Network accessline 6
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# 并发获取所有数据(使用不同的 id) curl ... '{"id":1,...}' & - Network accessline 74
curl ... '{"id":1,...}' & - Network accessline 75
curl ... '{"id":2,...}' & - Network accessline 76
curl ... '{"id":3,...}' & - Network accessline 77
curl ... '{"id":4,...}' & - Network accessline 78
curl ... '{"id":5,...}' & - Network accessline 79
curl ... '{"id":6,...}' & - Network accessline 85
(curl ... '{"id":1,...}' && curl ... '{"id":2,...}' && ...) - Network accessline 105
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**现象**:curl 请求超时或无响应 - Network accessline 141
1. 检查网络连接 2. 验证 API Key 是否有效 3. 检查 Sorftime 服务状态:`curl -I https://mcp.sorftime.com` - Network accessline 142
2. 验证 API Key 是否有效 3. 检查 Sorftime 服务状态:`curl -I https://mcp.sorftime.com` 4. 增加超时时间:`curl --max-time 30` - Network accessline 143
3. 检查 Sorftime 服务状态:`curl -I https://mcp.sorftime.com` - Network accessline 144
4. 增加超时时间:`curl --max-time 30`
SKILLS/skills/keyword-research/references/sorftime-mcp-api.md
SKILLS/skills/keyword-research/scripts/csv_generator.py
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#!/usr/bin/env python3
SKILLS/skills/keyword-research/scripts/data_parser.py
SKILLS/skills/keyword-research/scripts/generate_html_dashboard.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 322
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>关键词调研分析 - {{ASIN}} ({{SITE}})</title> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> - Network accessline 323
<title>关键词调研分析 - {{ASIN}} ({{SITE}})</title> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> <style> - Network accessline 324
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> - Network accessline 478
<h1>关键词调研分析仪表板</h1> <div class="meta"> ASIN: <a href="https://www.amazon.com/dp/{{ASIN}}" target="_blank" style="color: white;">{{ASIN}}</a> | - Network accessline 479
<div class="meta"> ASIN: <a href="https://www.amazon.com/dp/{{ASIN}}" target="_blank" style="color: white;">{{ASIN}}</a> | 产品: {{PRODUCT_NAME}} | - Network accessline 480
ASIN: <a href="https://www.amazon.com/dp/{{ASIN}}" target="_blank" style="color: white;">{{ASIN}}</a> |
SKILLS/skills/keyword-research/scripts/generate_markdown_report.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 100
| 项目 | 详情 | |------|------| | **ASIN** | [{asin}](https://www.amazon.com/dp/{asin}) | - Network accessline 101
|------|------| | **ASIN** | [{asin}](https://www.amazon.com/dp/{asin}) | | **产品名称** | {product_name} | - Network accessline 102
| **ASIN** | [{asin}](https://www.amazon.com/dp/{asin}) |
SKILLS/skills/keyword-research/scripts/keyword_collector.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/keyword-research/scripts/regen_md_html.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/keyword-research/scripts/regenerate_reports.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/keyword-research/scripts/test_html_gen.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/keyword-research/scripts/test_load_classify.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/keyword-research/scripts/workflow.py
SKILLS/skills/keyword-research/templates/dashboard_template.html
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<h1>关键词调研分析仪表板</h1> <div class="meta"> ASIN: <a href="https://www.amazon.com/dp/{{ASIN}}" target="_blank" style="color: white;">{{ASIN}}</a> | - Network accessline 226
<div class="meta"> ASIN: <a href="https://www.amazon.com/dp/{{ASIN}}" target="_blank" style="color: white;">{{ASIN}}</a> | 产品: {{PRODUCT_NAME}} | - Network accessline 227
ASIN: <a href="https://www.amazon.com/dp/{{ASIN}}" target="_blank" style="color: white;">{{ASIN}}</a> |
SKILLS/skills/product-research/SKILL.md
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2. **检查原始响应**: 查看 SSE 响应的实际内容 3. **分步执行**: 使用 Python 交互式环境逐行调试 4. **验证API Key**: `curl "https://mcp.sorftime.com?key=YOUR_KEY" -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'` - Network accessline 603
4. **验证API Key**: `curl "https://mcp.sorftime.com?key=YOUR_KEY" -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'`
SKILLS/skills/product-research/references/api-quick-reference.md
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SKILLS/skills/product-research/references/api-reference.md
SKILLS/skills/product-research/references/sorftime-mcp-api.md
SKILLS/skills/product-research/references/troubleshooting.md
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# 验证 API Key curl "https://mcp.sorftime.com?key=YOUR_KEY" \ - Network accessline 87
curl "https://mcp.sorftime.com?key=YOUR_KEY" \ - Network accessline 92
**解决方案**: 1. 检查 `.mcp.json` 文件 2. 确认 URL 格式: `https://mcp.sorftime.com?key=XXX` - Network accessline 93
1. 检查 `.mcp.json` 文件 2. 确认 URL 格式: `https://mcp.sorftime.com?key=XXX` 3. 获取新 API Key: https://sorftime.com/zh-cn/mcp - Network accessline 94
2. 确认 URL 格式: `https://mcp.sorftime.com?key=XXX` - Network accessline 95
3. 获取新 API Key: https://sorftime.com/zh-cn/mcp - Network accessline 233
### 使用 curl 直接测试 - Network accessline 236
# 测试类目搜索 curl -s -X POST "https://mcp.sorftime.com?key=YOUR_KEY" \ - Network accessline 237
curl -s -X POST "https://mcp.sorftime.com?key=YOUR_KEY" \
SKILLS/skills/product-research/scripts/api_client.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 58
[Credential-related source omitted] - Network accessline 74
# 从 URL 中提取 API key: https://mcp.sorftime.com?key=XXX - Access to secretsline 77
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try: result = subprocess.run( ['curl', '-s', '-X', 'POST', self.api_url, - Network accessline 356
result = subprocess.run( ['curl', '-s', '-X', 'POST', self.api_url, '-H', 'Content-Type: application/json',
SKILLS/skills/product-research/scripts/collect_data.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/product-research/scripts/fix_data_json.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/product-research/scripts/get_reviews.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/product-research/scripts/render_dashboard.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 66
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>{{CATEGORY}} - {{SITE}} 选品分析看板</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script> - Network accessline 67
<title>{{CATEGORY}} - {{SITE}} 选品分析看板</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script> <style> - Network accessline 68
<script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
SKILLS/skills/product-research/scripts/run_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/product-research/scripts/validate_data.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/product-research/scripts/verify_reviews.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/review-analysis/SKILL.md
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# 从 JSON 中提取 API 密钥 # 格式: "url": "https://mcp.sorftime.com?key={API_KEY}" - Network accessline 60
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**如果返回 "Authentication required" 或 "授权失败"**: - 告知用户 API 密钥无效或已过期 - 指引用户访问 https://sorftime.com/zh-cn/mcp 获取新密钥 - Network accessline 85
- 告知用户 API 密钥无效或已过期 - 指引用户访问 https://sorftime.com/zh-cn/mcp 获取新密钥 - 更新 `.mcp.json` 文件 - Network accessline 86
- 指引用户访问 https://sorftime.com/zh-cn/mcp 获取新密钥 - Network accessline 99
# 获取差评(1-3星),保存原始SSE响应 curl -s -X POST "https://mcp.sorftime.com?key=${API_KEY}" \ - Network accessline 100
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**解决方案**: 1. 访问 https://sorftime.com/zh-cn/mcp 获取新密钥 - Network accessline 424
1. 访问 https://sorftime.com/zh-cn/mcp 获取新密钥
SKILLS/skills/review-analysis/设计文档.md
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│ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ │ │ │ API调用 │ │ 文件解析 │ │ 痛点分类 │ │ Markdown │ │ │ │ curl │ │ JSON │ │ 情感分析 │ │ 模板渲染 │ │ - Network accessline 31
│ │ API调用 │ │ 文件解析 │ │ 痛点分类 │ │ Markdown │ │ │ │ curl │ │ JSON │ │ 情感分析 │ │ 模板渲染 │ │ │ └─────────┘ └─────────┘ └─────────┘ └─────────┘ │ - Network accessline 32
│ │ curl │ │ JSON │ │ 情感分析 │ │ 模板渲染 │ │ - Network accessline 99
▼ ┌─────────────────────────────────────────────────────────┐ │ Step 2: 获取评论数据 (curl product_reviews API) │ - Network accessline 100
┌─────────────────────────────────────────────────────────┐ │ Step 2: 获取评论数据 (curl product_reviews API) │ │ → 02_reviews_raw.txt (SSE 格式原始响应) │ - Network accessline 101
│ Step 2: 获取评论数据 (curl product_reviews API) │ - Network accessline 282
| 方面 | amazon-analyse | review-analysis | |------|----------------|-----------------| | 数据获取 | curl API | curl API (相同) | - Network accessline 283
|------|----------------|-----------------| | 数据获取 | curl API | curl API (相同) | | 数据解析 | SSE 解码 | SSE 解码 (相同) | - Network accessline 284
| 数据获取 | curl API | curl API (相同) | - Network accessline 389
*文档版本: v2.0 (LLM Agent 架构)* *最后更新: 2026-03-15* *参考资料有: https://mp.weixin.qq.com/s/agrml8THPvCmMxOMMmxKzA - Network accessline 391
*参考资料有: https://mp.weixin.qq.com/s/agrml8THPvCmMxOMMmxKzA
SKILLS/skills/sellersprite-amazon-research/README.md
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This skill integrates **SellerSprite (卖家精灵)** — a leading Amazon analytics platform — with AI assistants (Claude Code) via the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/). It enables natural-language-driven, end-to-end - Network accessline 23
- [Claude Code](https://claude.ai/code) CLI - Network accessline 41
"mcpServers": { "sellersprite": { "url": "https://mcp.sellersprite.com/mcp", - Network accessline 42
"sellersprite": { "url": "https://mcp.sellersprite.com/mcp", "headers": { - Network accessline 43
"url": "https://mcp.sellersprite.com/mcp", - Network accessline 63
/research https://www.amazon.com/dp/B08R8FSFRB
SKILLS/skills/sellersprite-amazon-research/scripts/competitor_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 6
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 7
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 17
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 18
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 19
req = urllib.request.Request(URL, data=payload, - Network accessline 21
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=180) as resp: - Network accessline 22
try: with urllib.request.urlopen(req, timeout=180) as resp: raw = resp.read().decode('utf-8') - Network accessline 23
with urllib.request.urlopen(req, timeout=180) as resp:
SKILLS/skills/sellersprite-amazon-research/scripts/dji_pocket3_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 6
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 7
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 16
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 17
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 18
req = urllib.request.Request(URL, data=payload, - Network accessline 20
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=180) as resp: - Network accessline 21
try: with urllib.request.urlopen(req, timeout=180) as resp: raw = resp.read().decode('utf-8') - Network accessline 22
with urllib.request.urlopen(req, timeout=180) as resp:
SKILLS/skills/sellersprite-amazon-research/scripts/fix_keyword_report.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/sellersprite-amazon-research/scripts/keyword_deep_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/sellersprite-amazon-research/scripts/keyword_research.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 6
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 7
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 16
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 17
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 18
req = urllib.request.Request(URL, data=payload, - Network accessline 20
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=180) as resp: - Network accessline 21
try: with urllib.request.urlopen(req, timeout=180) as resp: raw = resp.read().decode('utf-8') - Network accessline 22
with urllib.request.urlopen(req, timeout=180) as resp:
SKILLS/skills/sellersprite-amazon-research/scripts/lavalier_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 6
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 7
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 18
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 19
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 20
req = urllib.request.Request(URL, data=payload, - Network accessline 22
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=180) as resp: - Network accessline 23
try: with urllib.request.urlopen(req, timeout=180) as resp: raw = resp.read().decode('utf-8') - Network accessline 24
with urllib.request.urlopen(req, timeout=180) as resp:
SKILLS/skills/sellersprite-amazon-research/scripts/mcp_call.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 5
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 6
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 15
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 16
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 17
req = urllib.request.Request(URL, data=payload, - Network accessline 19
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=120) as resp: - Network accessline 20
try: with urllib.request.urlopen(req, timeout=120) as resp: raw = resp.read().decode('utf-8') - Network accessline 21
with urllib.request.urlopen(req, timeout=120) as resp:
SKILLS/skills/sellersprite-amazon-research/scripts/review_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 8
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 9
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 19
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 20
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 21
req = urllib.request.Request(URL, data=payload, - Network accessline 23
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=180) as resp: - Network accessline 24
try: with urllib.request.urlopen(req, timeout=180) as resp: raw = resp.read().decode('utf-8') - Network accessline 25
with urllib.request.urlopen(req, timeout=180) as resp:
SKILLS/skills/sellersprite-amazon-research/scripts/tactical_strategies.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 6
SECRET_KEY = "" URL = "https://mcp.sellersprite.com/mcp" - Network accessline 7
URL = "https://mcp.sellersprite.com/mcp" - Network accessline 17
"params": {"name": name, "arguments": arguments} }).encode('utf-8') req = urllib.request.Request(URL, data=payload, - Network accessline 18
}).encode('utf-8') req = urllib.request.Request(URL, data=payload, headers={"Content-Type": "application/json", "secret-key": SECRET_KEY, - Network accessline 19
req = urllib.request.Request(URL, data=payload, - Network accessline 21
"Accept": "application/json, text/event-stream"}) try: with urllib.request.urlopen(req, timeout=180) as resp: - Network accessline 22
try: with urllib.request.urlopen(req, timeout=180) as resp: raw = resp.read().decode('utf-8') - Network accessline 23
with urllib.request.urlopen(req, timeout=180) as resp:
SKILLS/skills/sellersprite-amazon-research/skill.md
- Network accessline 14
"mcpServers": { "sellersprite": { "url": "https://mcp.sellersprite.com/mcp", - Network accessline 15
"sellersprite": { "url": "https://mcp.sellersprite.com/mcp", "headers": { - Network accessline 16
"url": "https://mcp.sellersprite.com/mcp", - Network accessline 25
| 配置项 | 正确值 | 错误值 | |--------|--------|--------| | URL | `https://mcp.sellersprite.com/mcp` | `.../sse` 或 `.../mcp?key=xxx` | - Network accessline 26
|--------|--------|--------| | URL | `https://mcp.sellersprite.com/mcp` | `.../sse` 或 `.../mcp?key=xxx` | | 认证方式 | `headers.secret-key` | URL 查询参数 `?key=` | - Network accessline 27
| URL | `https://mcp.sellersprite.com/mcp` | `.../sse` 或 `.../mcp?key=xxx` | - Network accessline 47
curl -s -X POST "https://mcp.sellersprite.com/mcp" \ - Network accessline 64
"params":{"name":"market_research","arguments":{"request":{ "marketplace":"US","nodeIdPath":"...","topNum":10}}}}).encode() req = urllib.request.Request("https://mcp.sellersprite.com/mcp", data=payload, - Network accessline 65
"marketplace":"US","nodeIdPath":"...","topNum":10}}}}).encode() req = urllib.request.Request("https://mcp.sellersprite.com/mcp", data=payload, headers={"Content-Type":"application/json","secret-key":"<KEY>"}) - Network accessline 66
req = urllib.request.Request("https://mcp.sellersprite.com/mcp", data=payload, - Network accessline 67
headers={"Content-Type":"application/json","secret-key":"<KEY>"}) with urllib.request.urlopen(req) as resp: data = json.loads(resp.read().decode('utf-8')) - Network accessline 68
with urllib.request.urlopen(req) as resp:
SKILLS/skills/xiyou-insight/scripts/dashboard_generator.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 27
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>{{TITLE}}</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script> - Network accessline 28
<title>{{TITLE}}</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script> <style> - Network accessline 29
<script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
SKILLS/skills/xiyou-insight/scripts/data_aggregator.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/xiyou-insight/scripts/report_generator.py
- Executable scriptline 1
#!/usr/bin/env python3
SKILLS/skills/xiyou-insight/scripts/scenarios/__init__.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/ad_budget.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/ad_monitoring.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/base.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/competitor_analysis.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/keyword_database.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/new_product.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/scenarios/traffic_gap.py
- Executable scriptline 1
Executable file
SKILLS/skills/xiyou-insight/scripts/workflow.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 193
'stars': 4.5, 'ratings': 12580, 'url': f'https://www.amazon.com/dp/{asin}', - Network accessline 194
'ratings': 12580, 'url': f'https://www.amazon.com/dp/{asin}', 'image': 'https://example.com/image.jpg' - Network accessline 195
'url': f'https://www.amazon.com/dp/{asin}', - Network accessline 196
'image': 'https://example.com/image.jpg'
SKILLS/skills/xiyou-insight/scripts/workflow_competitor_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 110
'stars': 4.5, 'ratings': 12580, 'url': f'https://www.amazon.com/dp/{asin}', - Network accessline 111
'ratings': 12580, 'url': f'https://www.amazon.com/dp/{asin}', 'image': 'https://example.com/image.jpg' - Network accessline 112
'url': f'https://www.amazon.com/dp/{asin}', - Network accessline 113
'image': 'https://example.com/image.jpg'
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Declared and executed: 3 facts
- Contacts cdn.jsdelivr.net, which SKILL.md, the README and the plugin manifest do not mentionkeyword-research/scripts/generate_html_dashboard.py:324High confidence
- Contacts cdn.jsdelivr.net, which SKILL.md, the README and the plugin manifest do not mentionproduct-research/scripts/render_dashboard.py:68High confidence
- Contacts cdn.jsdelivr.net, which SKILL.md, the README and the plugin manifest do not mentionxiyou-insight/scripts/dashboard_generator.py:29High confidence
Signal confidence: 488 facts
- Network access in code of documentationamazon-analyse/README.md:141Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/README.md:141Low confidence
- Network access in code of documentationamazon-analyse/README.md:157Low confidence
- Network access in code of documentationamazon-analyse/README.md:158Low confidence
- Network access in code of documentationamazon-analyse/README.md:159Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/README.md:159Low confidence
- Network access in prose of documentationamazon-analyse/README.md:169Low confidence
- Network access in prose of documentationamazon-analyse/README.md:210Low confidence
- Network access in prose of documentationamazon-analyse/README.md:212Low confidence
- Network access in prose of documentationamazon-analyse/README.md:276Low confidence
- Network access in prose of documentationamazon-analyse/README.md:277Low confidence
- Network access in prose of documentationamazon-analyse/README.md:278Low confidence
- Network access in prose of documentationamazon-analyse/README.md:279Low confidence
- Network access in code of the SKILL.mdamazon-analyse/SKILL.md:23High confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valueamazon-analyse/SKILL.md:23Low confidence
- Network access in prose of the SKILL.mdamazon-analyse/SKILL.md:52Low confidence
- Network access in prose of the SKILL.mdamazon-analyse/SKILL.md:53Low confidence
- Network access in code of the SKILL.mdamazon-analyse/SKILL.md:67High confidence
- Network access in code of the SKILL.mdamazon-analyse/SKILL.md:68High confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valueamazon-analyse/SKILL.md:68Low confidence
- Network access in prose of the SKILL.mdamazon-analyse/SKILL.md:80Low confidence
- Network access in code of the SKILL.mdamazon-analyse/SKILL.md:84High confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valueamazon-analyse/SKILL.md:84Low confidence
- Network access in prose of the SKILL.mdamazon-analyse/SKILL.md:312Low confidence
- Network access in prose of documentationamazon-analyse/references/api-tools-reference.md:1Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:6Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:6Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:17Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:17Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:24Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:24Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:31Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:31Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:39Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:39Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:46Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:46Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:53Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:53Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:61Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valueamazon-analyse/references/api-tools-reference.md:61Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:73Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:74Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:75Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:76Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:77Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:78Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:79Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:85Low confidence
- Network access in code of documentationamazon-analyse/references/api-tools-reference.md:105Low confidence
and 438 more
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Native | Path CLAUDE.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md SKILLS/skills/amazon-analyse/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md SKILLS/skills/amazon-analyse/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md SKILLS/skills/amazon-analyse/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md SKILLS/skills/amazon-analyse/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md SKILLS/skills/amazon-analyse/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.
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