Skip to content
cccskills
FreePublished on GitHub

grants

Grant writing and proposal architecture: funder fit, proposal structure, budget design, and success-factor scoring. Use when writing a grant proposal, evaluating funder fit, auditing a draft for competitiveness, or planning a budget.

The English summary is being prepared. Showing the original description.

See how to install

Files included (7)

  • SKILL.md6.9 KB
  • references/budget-design-and-justification.md7.2 KB
  • references/funder-fit-and-research-strategy.md6.6 KB
  • references/proposal-structure-and-narrative.md7.8 KB
  • scripts/budget_realism_checker.py9.7 KB
  • scripts/funder_fit_scorer.py7.4 KB
  • scripts/proposal_structure_validator.py8.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Grant Writing & Proposal Architecture

A skill for crafting competitive grant proposals across funder types: government (NIH, NSF, DOE, ARPA), foundation, corporate, philanthropic, and SBIR / STTR. Focuses on the architecture of a winning proposal: fit, structure, narrative, budget — not boilerplate templating.

When to use this skill

  • Evaluating funder fit before investing weeks in a proposal
  • Designing the proposal structure for a specific funder
  • Writing or auditing the narrative for competitiveness
  • Designing a realistic, defensible budget
  • Pre-submission proposal review for common failure modes
  • Building a grants strategy (which to apply to over the year)

Inputs the advisor expects

  • The funder name + specific program / RFP
  • The research / project idea (problem, approach, outcomes)
  • Team composition (PI, co-investigators, key personnel)
  • Institutional / org context
  • Past funding history
  • Budget envelope (or constraint)
  • Submission deadline

Clarify First

Before generating the proposal, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Funder + specific program / RFP — sets the mental model (NIH 5-criteria vs NSF merit+impact vs foundation mission fit); drives structure and narrative
  • Project idea (problem, approach, outcomes) — drives the significance/innovation narrative and the Heilmeier answers
  • Budget envelope — drives budget design and whether scope matches the funder's typical award size
  • Team composition (PI, key personnel) — drives the investigator/environment fit dimension

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflows

Workflow 1 — Score funder fit before committing

  1. Capture funder, program, project idea, team strengths.
  2. Run funder_fit_scorer.py to grade fit on 7 dimensions.
  3. If fit < 65, look for better-aligned funder; don't waste 4 weeks.
python3 grants/scripts/funder_fit_scorer.py \
  --input funder_fit.json --format markdown

Workflow 2 — Validate proposal structure against funder expectations

  1. Capture the proposal section list + page allocation.
  2. Run proposal_structure_validator.py against funder type expectations.
  3. Adjust before drafting deep.
python3 grants/scripts/proposal_structure_validator.py \
  --input proposal_structure.json --funder-type nih --format markdown

Workflow 3 — Audit budget for realism

  1. Capture budget line items with justifications.
  2. Run budget_realism_checker.py against funder norms + project scope.
  3. Adjust before submission.
python3 grants/scripts/budget_realism_checker.py \
  --input budget.json --format markdown

Decision frameworks

Funder fit dimensions

  1. Topic alignment — does the funder fund this area?
  2. Mechanism alignment — does the funder fund this kind of work (R&D, services, scale-up)?
  3. Stage alignment — early-stage / mid / scale?
  4. Geographic alignment — does the funder fund your region?
  5. Team profile alignment — does the funder fund your kind of team?
  6. Budget envelope alignment — does the funder's typical award size match?
  7. Competitive density — is it 5% acceptance or 35%?

A score below 65 across these is usually a "skip this funder" signal.

Funder type — distinct mental models

Funder typeEmphasizesDe-emphasizes
NIHSignificance + innovation + approach + investigator + environment (5 criteria)Commercial outcome
NSFIntellectual merit + broader impactsDirect commercial outcome
ARPA / DARPAHeilmeier catechism (defined moonshot question)Incremental work
SBIR / STTRCommercial path + technical riskPure science
FoundationMission fit + measurable outcomesPure academic novelty
CorporateCommercial relevance to sponsorIndependence from sponsor
CrowdfundingStory + community appealTechnical rigor

Write to the funder's mental model, not a generic "good grant."

The Heilmeier catechism (good for any proposal)

  1. What are you trying to do?
  2. How is it done today; what are the limits?
  3. What's new in your approach; why succeed?
  4. Who cares; if you succeed, what difference does it make?
  5. What are the risks; how will you mitigate?
  6. How much will it cost; how long?
  7. What are the mid-term + final outcomes you'll deliver?

A proposal that can't answer all seven crisply isn't ready.

Common engagements

"Help me decide between two RFPs"

  1. Score both for fit; the higher one is usually right.
  2. If close: which has earlier deadline / smaller proposal effort?
  3. Don't submit to both same year unless funders are independent.

"Audit my draft proposal"

  1. Check funder-fit assumptions (did the program actually fund what you're proposing?)
  2. Check structure against funder template
  3. Check narrative: is the problem compelling? approach novel?
  4. Check budget: realistic + justified
  5. Check team credentials: matches scope?
  6. Read for: jargon, vague claims, unjustified assumptions

"We've never applied for an NIH R01. What's the prep?"

  1. Smaller grant first (R21, K, F32) if eligible — build track record
  2. Talk to a program officer before drafting (essential)
  3. Pre-submission inquiry where allowed
  4. Get a mock review from someone who's reviewed for NIH

Anti-patterns to avoid

  • Applying without funder fit. Wastes 4-8 weeks.
  • Generic proposal sent to multiple funders. Each wants a specific mental model.
  • Budget that doesn't match scope. Reviewer red flag.
  • Vague significance statement. "This is important" without specifics.
  • No risk discussion. Reviewers know there's risk; not acknowledging it = naive.
  • Team without right credentials. Match key personnel to scope.
  • Submitting at last minute. Errors; missed letters of support.

References

  • references/funder-fit-and-research-strategy.md — fit dimensions, funder types, multi-funder strategy
  • references/proposal-structure-and-narrative.md — per-funder structures, narrative discipline
  • references/budget-design-and-justification.md — budget categories, indirect costs, common errors

Related skills

  • research/litreview — literature review for proposals
  • c-level-advisor/general-counsel-advisor — legal review of terms
  • c-level-advisor/cfo-advisor — financial review

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".

The English summary is being prepared. Showing the original description.

borghei/Claude-Skills962Updated Oct 7, 2026

Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."

The English summary is being prepared. Showing the original description.

borghei/Claude-Skills962Updated Oct 7, 2026

Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.

The English summary is being prepared. Showing the original description.

borghei/Claude-Skills962Updated Oct 7, 2026

Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.

The English summary is being prepared. Showing the original description.

borghei/Claude-Skills962Updated Oct 7, 2026

Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.

The English summary is being prepared. Showing the original description.

borghei/Claude-Skills962Updated Oct 7, 2026

aeo

Free

Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.

The English summary is being prepared. Showing the original description.

borghei/Claude-Skills962Updated Oct 7, 2026

See all skills by borghei

Report a problem with this skill