template-academic-paper
Template-native manuscript planning, outline, drafting, revision, formatting, citation check, and AI-use disclosure routing. USE WHEN the user asks to write, outline, revise, format, or prepare a paper inside the Research Project Template.
Best use case
template-academic-paper is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Template-native manuscript planning, outline, drafting, revision, formatting, citation check, and AI-use disclosure routing. USE WHEN the user asks to write, outline, revise, format, or prepare a paper inside the Research Project Template.
Teams using template-academic-paper should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/academic-paper/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How template-academic-paper Compares
| Feature / Agent | template-academic-paper | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Template-native manuscript planning, outline, drafting, revision, formatting, citation check, and AI-use disclosure routing. USE WHEN the user asks to write, outline, revise, format, or prepare a paper inside the Research Project Template.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Academic paper Template-native paper workflow. It uses project manuscript sources, generated variables, validation gates, and evidence registries rather than a copied external academic agent prompt. ## Natural invoke - "Help me plan this paper" - "Write the outline and methods section from these artifacts" - "Revise the manuscript after reviewer comments" - "Check citations and convert the final paper format" - "Write an AI-use disclosure tied to the repo evidence" ## Inputs to confirm - **Project** - resolve through `docs/_generated/active_projects.md`. - **Mode** - plan, outline, full, revision, format, citation-check, or disclosure. - **Manuscript style** - Pandoc-crossref or registry tokens; do not mix styles. - **Evidence sources** - generated variables, claim ledger, figures, tables, references, validation reports. ## Workflow 1. **Plan first when uncertain** - capture target venue, paper type, contribution, section map, and unresolved material gaps. 2. **Draft from artifacts** - write against `projects/<project>/manuscript/`, generated variables, figure captions, and citekeys; use `[MATERIAL GAP]` instead of fabricating missing evidence. 3. **Preserve injected values** - prefer `[[VAR:...]]`, registry-backed labels, citekeys, and project-defined cross-reference tokens over hard-coded numbers. 4. **Validate continuously** - run prerender, markdown, citation, PDF, and integrity checks appropriate to the mode. 5. **Handoff for review** - use [academic-paper-reviewer](../academic-paper-reviewer/SKILL.md) for read-only critique; use claim verification before finalization. ## Deliverables - Plan mode: section outline, evidence map, unresolved gaps, and commands to validate. - Full/revision mode: source-layer manuscript edits, response notes, and validation status. - Format/citation mode: citation audit, render-safe changes, and output paths. - Disclosure mode: concise AI-use disclosure grounded in project evidence and human review checkpoints. ## Verification commands ```bash uv run python -m infrastructure.validation.cli prerender projects/<project>/manuscript --repo-root . uv run python -m infrastructure.reference.citation validate projects/<project>/manuscript/references.bib uv run python -m infrastructure.validation.cli markdown projects/<project>/manuscript --repo-root . --strict uv run python -m infrastructure.validation.cli integrity output/<project>/ ``` ## References - [MODE_REGISTRY.md](../MODE_REGISTRY.md) - [manuscript-creation](../manuscript-creation/SKILL.md) - [manuscript-claim-verification](../manuscript-claim-verification/SKILL.md)
Related Skills
template-validation-quality
Run validation CLI, prerender, markdown/PDF/integrity gates, and QA workflows for the Research Project Template. USE WHEN validate manuscript, check PDF for ?? refs, prerender gate, link checker, output integrity, or pre-commit validation — even without validation_quality prompt.
template-test-creation
Create pytest suites under the no-mocks policy — real data, temp files, subprocess, pytest-httpserver. USE WHEN adding tests, raising coverage, testing new src/ module, or user forbids mocks.
template-reproducibility-audit
Deterministic reproducibility audit — fixed seeds, regenerate-from-clean, double-run diff before Zenodo/arXiv/release. USE WHEN outputs drift between runs, "worked on my machine", need regenerate-from-clean proof, or pre-release reproducibility check — even without naming docs/prompts.
template-refactoring
Clean-break refactors with migration for the Research Project Template — move logic to src/, split modules, rename APIs with test updates. USE WHEN restructuring code, extracting modules, removing duplication, or migration without behavior change.
template-pipeline-debugging
Systematic pipeline DAG failure triage for the Research Project Template. USE WHEN ./run.sh or execute_pipeline.py fails, a stage stalls (setup, tests, analysis, render, validate, LLM, copy), pytest/coverage gate fails mid-pipeline, PDF render or validate breaks, Project Analysis finishes too fast with no figures, or user says pipeline debug, stage failed, resume checkpoint, core-only triage — even without naming this skill or docs/prompts.
template-methods-orchestration
Repo-wide methods orchestration workflow for the Research Project Template. USE WHEN the user asks to add, audit, improve, or validate methods, methodology, method contracts, stage-to-method wiring, artifact/evidence provenance, or orchestration across template projects.
template-manuscript-cross-references
Audit or author registry-driven manuscript cross-refs — labels.yaml, [[FIG:]], [[THMREF:]], [[VAR:]] tokens. USE WHEN fixing figure/equation/theorem numbering, orphan registry keys, hard-coded "Theorem 7.3" in prose, or [[MISSING:]] injection failures — even for Pandoc projects that also use a YAML registry.
template-manuscript-creation
Scaffold a research manuscript and project layout from a research brief — sections, config.yaml, src/, scripts/, tests. USE WHEN starting a new paper, new projects/ tree, manuscript from topic description, or aligning with template_code_project exemplar — even without copy-paste prompts.
template-manuscript-claim-verification
Triple-pass verification of every manuscript claim against code, data, refs, and renderer; repair prose while staying renderable. USE WHEN pre-submission, pre-Zenodo, pre-arXiv, abstract numbers disagree with CSV, citations do not support sentences, or user asks to triple-check / verify every claim — even without docs/prompts. Not for casual PDF summary.
template-feature-addition
End-to-end feature work across src/, scripts/, tests/, manuscript, and docs for the Research Project Template. USE WHEN adding a pipeline-visible feature, new analysis stage, manuscript-facing output, or cross-layer integration — even without feature_addition prompt.
template-documentation-creation
Author or refresh AGENTS.md and README.md for template directories — accurate commands, Mermaid where helpful, link _generated/active_projects.md. USE WHEN folder needs AGENTS, README audit, doc contract fix, or signposting after code change — even without documentation_creation prompt.
template-deep-research
Template-native research intake, literature search, source verification, synthesis, fact-checking, and systematic-review planning. USE WHEN the user asks to research a topic, build a literature corpus, fact-check claims, prepare a PRISMA-style review, or clarify a research question before manuscript work.