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hujizhou35-cmd/journal-cover-letter-tutorial

Research, Review & Bibliometrics cover-letter workflows. Writer v3.2 is free on Agensi; MIT open source.｜投稿信撰写与迭代教程

ResearchWritingEducation

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skills/journal-cover-letter-skill-trainer/SKILL.md

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View on GitHubAdd to my skills

Verified commit b1f2fc9e24ef2effd2e6abdf3ef3f2daaac77757

42GitHub stars
-1star in 7 days
2skills in this repository
0commits in 30 days

Heat

0.2
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Heat never changes the order by stars, and sponsorship never touches it. How heat works

Stars over time

Oct 25, 2026Nov 5, 202643

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Individual skills in this repository

How it works

journal-cover-letter-skill

When your agent uses it

Create, revise, benchmark, or check a cover letter for an academic journal submission from manuscript files. Use whenever a user wants a journal submission letter, asks to tailor a cover letter to a target journal, provides manuscript materials and asks for a letter, wants an existing academic cover letter improved, or submits a bibliometric/science-mapping manuscript. Route empirical research around one finding, evidence syntheses around what the synthesis changes in understanding, and bibliometric studies around what the map reveals about a field's structure or evolution. Do not use for job applications, recommendation letters, or business correspondence.

What it loads into context

Frontmatter

128 tokens

Always available to the agent

SKILL.md

3,673 tokens

When the skill is activated

Reference documents

9,522 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

  1. Core architecture: evidence anchor -> editorial meaning
  2. Core rules
  3. 1. Intake, routing, and fact sheet
  4. 2. Previous-letter permission and benchmark extraction
  5. 3. Author confirmation gate
  6. 4. Current journal research
  7. 5A. Original Research route
  8. 5B. Review and synthesis route
  9. 5C. Bibliometrics route
  10. 6. Evidence-to-meaning gate
  11. 7. Persuasion without overclaiming
  12. 8. Declarations
  13. 9. Bounded revision loops
  14. 10. Final gates and delivery
  15. Bundled tools and optional detail

Scripts executed separately

  • scripts/audit_cover_letter.py
  • scripts/extract_docx_content.py
  • scripts/generate_audit_report.py
  • scripts/render_cover_letter_docx.py
  • scripts/validate_payload.py

Files

  • SKILL.mdcore19,102 bytes
  • SKILL.mdcore19,102 bytes
  • agents/openai.yamlasset255 bytes
  • assets/cover-letter-payload.bibliometrics.example.jsonasset3,570 bytes
  • assets/cover-letter-payload.example.jsonasset2,278 bytes
  • assets/cover-letter-template.mddoc755 bytes
  • references/bibliometrics-playbook.mddoc10,035 bytes
  • references/blind-benchmark-loop.mddoc2,217 bytes
  • references/controlled-uplift.mddoc1,225 bytes
  • references/editorial-iteration-rubric.mddoc2,658 bytes
  • references/human-benchmark-protocol.mddoc4,531 bytes
  • references/intake-and-fact-sheet.mddoc2,550 bytes
  • references/journal-research-protocol.mddoc1,643 bytes
  • references/loop-controller.mddoc5,310 bytes
  • references/migration-v2.3-to-v3.0.mddoc1,080 bytes
  • references/migration-v3.0-to-v3.1.mddoc680 bytes
  • references/migration-v3.1-to-v3.2.mddoc604 bytes
  • references/output-and-docx.mddoc948 bytes
  • references/persuasion-calibration.mddoc1,641 bytes
  • references/research-playbook.mddoc7,831 bytes
  • references/review-playbook.mddoc4,736 bytes
  • references/submission-branches-and-declarations.mddoc1,339 bytes
  • scripts/audit_cover_letter.pyruns2,971 bytes
  • scripts/extract_docx_content.pyruns1,196 bytes
  • scripts/generate_audit_report.pyruns2,907 bytes
  • scripts/render_cover_letter_docx.pyruns4,586 bytes
  • scripts/validate_payload.pyruns6,967 bytes
Read SKILL.md

# Journal Cover Letter Skill v3.2

Turn verified manuscript facts into a clear editorial decision aid. Default to English unless the user requests another language. Prioritize biomedical and life-science submissions while remaining useful across disciplines.

## Core architecture: evidence anchor -> editorial meaning

Every persuasive claim must contain both parts:

- `empirical_anchor`: the concrete, manuscript-traceable observation selected for the editor;
- `editorial_meaning`: what that observation changes in understanding, interpretation, coordination, practice, or the next research decision.

For manuscripts with a distinctive empirical taxonomy, trend set, or named result pattern, also preserve an `authorial_empirical_fingerprint`: the minimum manuscript-native detail that lets an editor distinguish this paper from another paper on the same topic.

A letter fails when it offers facts without meaning, meaning without a traceable factual anchor, or a polished abstraction that erases the manuscript's empirical fingerprint. This is the central v3.1 rule.
View the complete source on GitHub

Skills included

  • journal-cover-letter-skill
  • journal-cover-letter-skill-trainer

Repository facts

License
MIT
Created
Aug 2, 2026
Last pushed
Oct 1, 2026
Forks
1
Open issues
0
Project activity
Active

Before you install

Local scripts

Automated signals, not a guarantee

Checked Nov 5, 2026

Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.

Show 3 notes
  • skills/journal-cover-letter-skill/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
  • skills/journal-cover-letter-skill-trainer/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
  • skills/journal-cover-letter-skill-trainer/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
Show all 10 signals by file

skills/journal-cover-letter-skill-trainer/scripts/evaluate_promotion.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill-trainer/scripts/prepare_blind_packet.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill-trainer/scripts/prepare_generator_packet.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill-trainer/scripts/validate_context_ledger.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill-trainer/scripts/validate_training_manifest.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill/scripts/audit_cover_letter.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill/scripts/extract_docx_content.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill/scripts/generate_audit_report.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill/scripts/render_cover_letter_docx.py

  • Executable scriptline 1
    #!/usr/bin/env python3

skills/journal-cover-letter-skill/scripts/validate_payload.py

  • Executable scriptline 1
    #!/usr/bin/env python3

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.

Signal confidence: 10 facts

Works with

Agent compatibility, from the files in this repository
AgentStatusEvidenceInstall to
Claude CodeCompatibleStandard SKILL.md skills/journal-cover-letter-skill/SKILL.md.claude/skills/<skill-name>/
CodexCompatibleStandard SKILL.md skills/journal-cover-letter-skill/SKILL.md.agents/skills/<skill-name>/
CursorCompatibleStandard SKILL.md skills/journal-cover-letter-skill/SKILL.md.cursor/skills/<skill-name>/
Gemini CLICompatibleStandard SKILL.md skills/journal-cover-letter-skill/SKILL.md.gemini/skills/<skill-name>/
GitHub CopilotCompatibleStandard SKILL.md skills/journal-cover-letter-skill/SKILL.md.github/skills/<skill-name>/
OpenCodeCompatibleStandard SKILL.md skills/journal-cover-letter-skill/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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