Individual skill
skill-upper
Capture and review Agent Skill observations, and create, run, diagnose, or iteratively improve Skill evaluations (evals) with the skill-up CLI. Use when the user asks to record explicitly attributed Skill usage or feedback; review observations or user-supplied traces/transcripts; turn an approved observation into a regression case; evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate from Anthropic evals.json. Plugin observation capture/review require either the Codex skill-up plugin or an observer-enabled DSH skill-up plugin. User-supplied external evidence can be reviewed without a plugin; evaluation remains multi-engine.
skills/skill-upper/SKILL.md
Source commit f2d726e5f61a57c378dbae001264bb4ed6f13967
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 3, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
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An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,439
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
README.mddoc · 2,969 bytesREADME.zh.mddoc · 2,579 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesSKILL.mdcore · 22,715 bytesassets/case.yaml.tmplasset · 3,499 bytesassets/eval.yaml.tmplasset · 3,424 bytesevals/README.mddoc · 492 bytesevals/cases/add-case-to-existing.yamlasset · 1,090 bytesevals/cases/credential-presence-only.yamlasset · 2,664 bytesevals/cases/english-context-generates-english-only-cases.yamlasset · 1,291 bytesevals/cases/evolve-existing-skill.yamlasset · 1,420 bytesevals/cases/external-trace-review.yamlasset · 1,368 bytesevals/cases/plan-without-mutation.yamlasset · 1,515 bytesevals/cases/preserve-localized-regressions.yamlasset · 1,307 bytesevals/cases/review-evolution-evidence.yamlasset · 2,498 bytesevals/cases/scaffold-new-evals.yamlasset · 1,575 bytesevals/cases/scaffold-with-qodercli-engine.yamlasset · 1,344 bytesevals/cases/scaffold-with-script-judge.yamlasset · 1,263 bytesevals/cases/scaffold-with-user-simulator.yamlasset · 2,172 bytesevals/eval-dashscope.yamlasset · 474 bytesevals/eval.yamlasset · 1,301 bytesevals/fixtures/scripts/assert-credential-presence.shruns · 35,156 bytesevals/fixtures/scripts/assert-english-only-generated-cases.shruns · 5,106 bytesevals/fixtures/scripts/assert-localized-regressions.shruns · 16,033 bytesevals/fixtures/scripts/assert-read-only-plan.shruns · 7,161 bytesevals/requirements.txtdoc · 15 bytesevals/test_regression_scripts.pyruns · 45,665 bytesreferences/case-yaml.mddoc · 5,789 bytesreferences/cli.mddoc · 5,595 bytesreferences/eval-yaml.mddoc · 9,074 bytesreferences/install.mddoc · 5,654 bytesreferences/judge-types.mddoc · 5,133 bytesreferences/migrate-anthropic.mddoc · 2,065 bytesreferences/observations.mddoc · 3,258 bytes
Read excerpt
# use-skill-up-cli
Help the user evaluate and evolve Agent Skills through the `skill-up` CLI.
Manual: <https://alibaba.github.io/skill-up/>
## Language Policy
**Default to English when responding to the user. If the user writes in Chinese (or any other language), switch to that language and stay consistent with the user's input throughout the session.**
Detection rules (highest priority first):
1. The user explicitly specifies a language in the current message (e.g. "answer in English" or "reply in Chinese") → follow the user's instruction.
2. The natural language used in the user's current message → match it.