Grant proposal
Skill pedrohcgs/claude-code-my-workflow/.claude/skills/grant-proposal
A ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.
npx -y skills add pedrohcgs/claude-code-my-workflow --skill grant-proposalAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Scaffold a research grant proposal (NSF, NIH, ERC, or foundation) by composing existing primitives — pulls identification strategy from an `/interview-me` spec, delegates the data-management plan to `/data-management-plan` and the facilities statement to `/capture-environment`, and emits a funder-requirements checklist. Use when user says "draft a grant", "write a proposal", "NSF proposal", "NIH aims", "ERC application", "foundation grant", "specific aims", or "scaffold a grant proposal". NOT a submission tool — produces a draft the user uploads to the sponsor's portal themselves.
SKILL.md
12.0 KB, as published. Nobody here has run it
/grant-proposal — Research Grant Proposal Scaffolder
Compose a funder-shaped grant proposal draft from primitives you already have: an /interview-me research spec supplies the science, /data-management-plan supplies the DMP, /capture-environment supplies the facilities/computational statement, and /lit-review supplies the prior-work framing. This skill structures and stitches — it does not submit anywhere, and it does not invent identification strategy where a spec is absent.
Core principle: A proposal is a coherence artifact. Aims, methods, budget, timeline, and broader impacts must agree with each other and with the underlying research spec. The skill's main value-add over a blank template is the Phase 3 coherence pass (aims ↔ methods ↔ budget ↔ timeline).
When to use
- Drafting an NSF / NIH / ERC / foundation proposal from an existing research idea.
- Turning an
/interview-mespec (or a/preregisterPAP) into a fundable narrative. - Assembling the boilerplate-but-required pieces (DMP, facilities, data-sharing) so the human writes only the science.
- During resubmission, re-scaffolding aims after a reviewer "revise and resubmit" round.
When NOT to use
- You need the science itself invented — run
/interview-mefirst; this skill refuses to fabricate an identification strategy. - The sponsor is a clinical-trial funder requiring its own protocol template (out of scope; use the sponsor's native forms).
- You want a finished, submittable PDF — this writes Markdown sections + a checklist; final assembly into the sponsor's format is yours.
Funder profiles
Generic across sponsors via placeholder profiles. --funder selects the section set + naming; default is nsf.
| Funder | Core sections (named per sponsor) | Page/format signals |
|---|---|---|
nsf | Project Summary (Overview/Intellectual Merit/Broader Impacts) · Project Description · Broader Impacts · Data Management & Sharing Plan · Facilities/Equipment · Budget Justification | 15-page Project Description; DMSP required |
nih | Specific Aims (1 p.) · Research Strategy (Significance/Innovation/Approach) · Vertebrate/Human Subjects (if any) · Data Management & Sharing · Facilities & Other Resources · Budget Justification | Aims page is load-bearing |
erc | Extended Synopsis (B1) · Scientific Proposal (B2: state-of-art, objectives, methodology) · CV + track record · Resources/Budget · Data Management | PI-centric; "high-risk/high-gain" framing |
foundation | Project Summary · Statement of Need · Goals & Objectives · Methods/Approach · Evaluation Plan · Budget Justification · Sustainability | Mission-fit framing; lighter methods |
Economics framing is the primary lens (DiD/event-study, IV, RCT, panel; AEA Data Editor / openICPSR / DCAS data-sharing expectations), but the section scaffold is field-agnostic — a biology or CS forker fills the same slots.
Workflow
Phase 0 — Detect funder + spec
- Resolve
--funder(or infer from the request wording; defaultnsf). Echo the chosen profile back before drafting. - Locate the research spec:
--input <path>, else the most recentquality_reports/specs/research_spec_*.mdfrom/interview-me. If none exists, stop and recommend/interview-me— do not invent the science. - From the spec, extract: research question, hypotheses (directional), identification strategy (DiD / IV / RDD / RCT / structural), data sources, sample, expected results, contribution. Record any
paper_type:field. - Scan
quality_reports/for adjacent artifacts to reuse: a/lit-reviewsynthesis (prior work), a/preregisterPAP (analysis plan), apassport.yamlor/data-analysisoutputs (preliminary results).
Phase 1 — Scaffold sections from templates + the spec
Generate the funder's section set. Map spec content into slots:
- Specific Aims / Project Summary — RQ + 2–3 numbered, directional aims drawn from the spec's hypotheses.
- Background & Significance — motivation + prior work; pull citations from the
/lit-reviewsynthesis if present (do not re-search unless asked). - Research Design & Methods — lift the identification strategy verbatim from the spec (estimand, treatment/control, identifying assumption, robustness: pre-trends, placebo, clustering). Name the estimator concretely (e.g.
fixest::feols,did::att_gt, Statacsdid). - Preliminary Results — summarize any existing
/data-analysis/ passport outputs; otherwise mark[PRELIMINARY RESULTS: none yet — describe planned pilot]. - Timeline & Milestones — quarter/year table aligned to the aims (every aim gets a milestone).
- Broader Impacts / Significance — sponsor-appropriate framing (NSF Broader Impacts vs NIH Significance vs foundation mission-fit).
- Budget Justification skeleton — personnel / data acquisition / compute / travel / dissemination line-item stubs, each tied to an aim.
For every MUST slot the spec did not supply, write [CLARIFY: <specific question>] — never fabricate. Re-use the MUST / SHOULD / MAY clarity language from templates/requirements-spec.md.
Phase 2 — Compose the DMP and computational statements (delegate)
- Data Management (& Sharing) Plan — invoke
/data-management-planviaTaskwith the funder + data sources from the spec. It returns the DMP section (repository choice — openICPSR / Dataverse / Zenodo, access/retention, FAIR/DCAS alignment). If any data source is sensitive (restricted-use admin data, PII, IRB-restricted), have it honor.claude/rules/confidential-data.mdand describe access via a secure enclave / FSRDC rather than open release. Do not draft a sharing plan that promises to release confidential data. - Facilities / Computational-Environment statement — invoke
/capture-environmentviaTaskto produce the compute/software/dependency statement (cluster, R/Stata/Python toolchain,renv.lock/DESCRIPTION/requirements.txtprovenance) for the Facilities section.
If a delegate skill is unavailable, leave a [DELEGATE: /data-management-plan] placeholder rather than half-writing its output.
Phase 3 — Coherence pass (aims ↔ methods ↔ budget ↔ timeline)
The differentiating step. Cross-check the assembled draft and report mismatches:
- Aims ↔ Methods — every aim has a named method/estimator; no orphan method serves no aim.
- Methods ↔ Budget — each cost line traces to an aim (e.g. an RCT aim implies a participant-incentives line; admin data implies an acquisition/enclave line; a large simulation implies a compute line).
- Aims ↔ Timeline — every aim has at least one milestone; no milestone is unattributed.
- DMP ↔ Methods — the data named in Methods matches the data described in the DMP; confidential sources are not promised as open.
- Page/format budget — flag sections likely to overflow the funder's page limit (NSF 15-page Project Description, NIH 1-page Aims).
Phase 4 — Post-flight verification + output
- Post-flight (CoVe): if Background/Significance cites prior literature, run the Post-Flight protocol from
.claude/rules/post-flight-verification.md— spawnclaim-verifierviaTask(context: fork) on the citations. Surface PASS / PARTIAL / FAIL. Skip on--no-verifyor zero citations. - Write sections to
--out(defaultquality_reports/grants/YYYY-MM-DD_<slug>/), one Markdown file per section pluschecklist.md.
Output / Report format
A proposal_draft.md (concatenated sections) plus a checklist.md:
# Grant Proposal Draft — [Title]
**Funder:** NSF | NIH | ERC | foundation **Date:** YYYY-MM-DD
**Source spec:** quality_reports/specs/research_spec_<slug>.md
## Funder-Requirements Checklist
| Requirement | Status | Source |
|---|---|---|
| Project Summary / Specific Aims | DRAFTED | Phase 1 |
| Research Design & Methods | DRAFTED | spec |
| Data Management & Sharing Plan | DELEGATED | /data-management-plan |
| Facilities / Computational Env | DELEGATED | /capture-environment |
| Budget Justification | SKELETON | Phase 1 |
| Broader Impacts / Significance | DRAFTED | Phase 1 |
| [n] [CLARIFY:] items unresolved | TODO | — |
## Coherence Report
- Aims ↔ Methods: PASS / [n issues]
- Methods ↔ Budget: PASS / [n issues]
- Aims ↔ Timeline: PASS / [n issues]
- DMP ↔ Methods (confidential-data check): PASS / [n issues]
- Page-budget flags: [sections at risk of overflow]
## Post-Flight Verification
Claims extracted: N · Verified: N · Outcome: PASS / PARTIAL / FAIL
Exit behavior
- All MUST slots filled + coherence PASS: report "DRAFT READY — review [CLARIFY:] items, then assemble in the sponsor's portal."
- Open [CLARIFY:] / [DELEGATE:] items or coherence issues: report "INCOMPLETE — N items unresolved" and list them. The skill never blocks like
/audit-reproducibility(it is a drafting tool, not a gate) — it surfaces, the author resolves. - No research spec found: stop in Phase 0 and recommend
/interview-me. Nothing is written.
Flags
--funder<nsf|nih|erc|foundation>— Select the funder profile that shapes section structure and the requirements checklist.--input<spec>— Path to an existing/interview-meresearch spec to seed Aims and Methods (otherwise the skill elicits them).
Cross-references
.claude/skills/interview-me/SKILL.md— produces the research spec this skill consumes; run it first if none exists..claude/skills/data-management-plan/SKILL.md— Phase 2 delegate for the DMP/DMSP section..claude/skills/capture-environment/SKILL.md— Phase 2 delegate for the facilities/computational statement..claude/skills/lit-review/SKILL.md— supplies Background & Significance prior-work framing..claude/skills/preregister/SKILL.md— a PAP can seed the analysis plan; preregistration is the forward commitment a funded project then executes..claude/rules/confidential-data.md— governs how sensitive data sources appear in the DMP and budget..claude/rules/post-flight-verification.md— Phase 4 citation fact-check.
What this skill does NOT do
- Submit anywhere. It writes Markdown + a checklist; you assemble and upload to Research.gov / ASSIST / the ERC portal / the foundation's system.
- Invent the science. No spec → no proposal. It will not fabricate an identification strategy, hypotheses, or aims.
- Write the DMP or facilities statement itself. Those are delegated to
/data-management-planand/capture-environment; this skill only stitches their output into the funder's section set. - Compute the budget. It scaffolds line items tied to aims; actual dollar figures, indirect-cost rates, and effort percentages are the PI's and the grants office's job.
- Guarantee page-limit compliance. It flags likely overflow; final trimming to the sponsor's exact format is manual.