/ai-research-writing-skill
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
$ npx -y skills add jin-s13/ai-research-writing-skill --skill ai-research-writing-skill --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ai-research-writing-skill
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
ai-research-writing-skill.SKILL.mdname: 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.
AI Research Writing Skill
Mandate
Treat paper writing as claim-evidence engineering, not prose generation.
- Ground claims in repository files, experiment artifacts, notes, or verified citations.
- Never invent citations or numeric results. Mark missing evidence visibly and weaken unsupported claims.
- For full papers, produce concrete LaTeX, BibTeX, figure, table, review, and build artifacts; do not stop at an outline.
- Keep human judgment in the loop for scientific correctness, visual inspection, reviewer risk, and final submission decisions.
Route the Task
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` | | Reviewer 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` |
Execution Contract
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.
Gates
- **Evidence**: exact numbers must trace to data, logs, tables, notebooks, or scripts. Quantitative papers maintain numeric-evidence v2 selectors and recomputable aggregates.
- **Story**: define thesis, gap, contribution boundary, and claims to avoid before a full draft.
- **Literature**: position close work before writing Related Work.
- **Citation**: scholarly `verified` records require `citation_requests.json` and a fresh `citation_lock.json`; metadata verification and sentence-level support are separate checks.
- **Figures**: generated images may explain concepts but cannot create numeric evidence. For overview, method, framework, pipeline, architecture, and teaser figures, use built-in image generation as the default paper asset; use deterministic plots/tables for results.
- **Review**: resolve high-severity reviewer objections or record them as blockers.
- **Build**: compile the real package with `record_build.py --run` before submission-ready; preserve command, log, tool version, exit code, and hashes.
- **Completion**: do not say "done" until required artifacts and checks pass or explicit blockers are reported.
Evidence Boundaries
- Treat negative, mixed, missing-seed, or incomplete results as scope constraints, not material to hide.
- Verify that each citation supports the attached sentence, not merely the topic.
- Save important papers locally only when access and redistribution permit; otherwise record stable metadata and access status.
- Generated diagrams communicate a workflow or idea; they are never experimental evidence.
Finish
Report the concrete artifacts changed, checks run, and remaining scientific risks. Preserve the author's intent, but not unsupported wording.
Read more
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.
AI Research Writing Skill
Mandate
Treat paper writing as claim-evidence engineering, not prose generation.
- Ground claims in repository files, experiment artifacts, notes, or verified citations.
- Never invent citations or numeric results. Mark missing evidence visibly and weaken unsupported claims.
- For full papers, produce concrete LaTeX, BibTeX, figure, table, review, and build artifacts; do not stop at an outline.
- Keep human judgment in the loop for scientific correctness, visual inspection, reviewer risk, and final submission decisions.
Route the Task
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` | | Reviewer 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` |
Execution Contract
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.
Gates
- **Evidence**: exact numbers must trace to data, logs, tables, notebooks, or scripts. Quantitative papers maintain numeric-evidence v2 selectors and recomputable aggregates.
- **Story**: define thesis, gap, contribution boundary, and claims to avoid before a full draft.
- **Literature**: position close work before writing Related Work.
- **Citation**: scholarly `verified` records require `citation_requests.json` and a fresh `citation_lock.json`; metadata verification and sentence-level support are separate checks.
- **Figures**: generated images may explain concepts but cannot create numeric evidence. For overview, method, framework, pipeline, architecture, and teaser figures, use built-in image generation as the default paper asset; use deterministic plots/tables for results.
- **Review**: resolve high-severity reviewer objections or record them as blockers.
- **Build**: compile the real package with `record_build.py --run` before submission-ready; preserve command, log, tool version, exit code, and hashes.
- **Completion**: do not say "done" until required artifacts and checks pass or explicit blockers are reported.
Evidence Boundaries
- Treat negative, mixed, missing-seed, or incomplete results as scope constraints, not material to hide.
- Verify that each citation supports the attached sentence, not merely the topic.
- Save important papers locally only when access and redistribution permit; otherwise record stable metadata and access status.
- Generated diagrams communicate a workflow or idea; they are never experimental evidence.
Finish
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.