prompt-lookup
Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use…
End-to-end research paper generation, review, and revision for ML/AI/CV/NLP projects from repositories, notes, experiment logs, drafts, and conference templates. Use when building a paper story, mapping claims to evidence, writing or revising sections, producing figures and
Claude Code
$ npx -y skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill --agent claude-code
Codex
$ npx skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill -a codex -y
Cursor
$ npx skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill -a cursor -y
Gemini CLI
$ npx skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill -a gemini-cli -y
GitHub Copilot
$ npx skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill -a github-copilot -y
OpenCode
$ npx skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill -a opencode -y
Windsurf
$ npx skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill -a windsurf -y
name: ai-research-writing-skill description: End-to-end research paper generation, review, and revision for ML/AI/CV/NLP projects from repositories, notes, experiment logs, drafts, and conference templates. Use when building a paper story, mapping claims to evidence, writing or revising sections, producing figures and tables, verifying citations, acting as a skeptical reviewer, running venue or build checks, or preparing a LaTeX/Overleaf/Git submission package.
Treat paper writing as claim-evidence engineering, not prose generation.
Choose the smallest route that covers the request. Load only the listed references first.
| Route | Load first | |---|---| | Full paper or major revision | `references/workflow.md`, `references/artifacts.md` | | Upstream research-system handoff | `references/research-handoff.md`, `references/artifacts.md` | | Story, thesis, gap, or contribution | `references/paper-story.md` | | Section writing or revision | `references/README.md`, then the section-specific reference | | Figures and tables | `references/figure-workflow.md`, `references/figure-spec.md` | | Citation search or repair | `references/citation-workflow.md` | | Peer review | `references/reviewer-guidelines.md` | | Author self-review or revision diagnosis | `references/reviewer-guidelines.md`, `references/reviewer-self-review.md` | | Submission or camera-ready audit | `references/submission-packaging.md`, `references/citation-checklist.md` | | Deterministic checks or formatting | `scripts/README.md` |
For full-paper and submission work:
1. Create `paper_state.json` from the contract in `references/artifacts.md`; declare mode, stage, venue, main TeX, bibliography, required artifacts, blockers, and build record. 2. If `research_handoff.json` exists, run `check_research_handoff.py --require-unblocked` first. Otherwise inventory the repository and experiments before drafting. Create one task packet and update `plan/progress.md` at the start and end. 3. Establish the story, claim boundaries, and literature position before long-form prose. 4. Follow the two-pass drafting order in `references/workflow.md`: write evidence-bearing core sections first, then finalize framing sections. 5. Run the mode-aware quality gate. A terminal stage is invalid when inputs are missing, claims/citations remain unresolved, verification is pending, blockers remain, or build hashes are stale.
Keep process instructions in plan/review files, never in manuscript prose.
Report the concrete artifacts changed, checks run, and remaining scientific risks. Preserve the author's intent, but not unsupported wording.
Turn an ML/AI research repo into an evidence-backed, build-ready conference paper draft. Point your coding agent at code, experiment logs, notes, and a venue template.
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