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".
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
Before generating the proposal, confirm these inputs. If any is unknown or vague, ASK — do not assume:
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.
funder_fit_scorer.py to grade fit on 7 dimensions.python3 grants/scripts/funder_fit_scorer.py \
--input funder_fit.json --format markdown
proposal_structure_validator.py against funder type expectations.python3 grants/scripts/proposal_structure_validator.py \
--input proposal_structure.json --funder-type nih --format markdown
budget_realism_checker.py against funder norms + project scope.python3 grants/scripts/budget_realism_checker.py \
--input budget.json --format markdown
A score below 65 across these is usually a "skip this funder" signal.
| Funder type | Emphasizes | De-emphasizes |
|---|---|---|
| NIH | Significance + innovation + approach + investigator + environment (5 criteria) | Commercial outcome |
| NSF | Intellectual merit + broader impacts | Direct commercial outcome |
| ARPA / DARPA | Heilmeier catechism (defined moonshot question) | Incremental work |
| SBIR / STTR | Commercial path + technical risk | Pure science |
| Foundation | Mission fit + measurable outcomes | Pure academic novelty |
| Corporate | Commercial relevance to sponsor | Independence from sponsor |
| Crowdfunding | Story + community appeal | Technical rigor |
Write to the funder's mental model, not a generic "good grant."
A proposal that can't answer all seven crisply isn't ready.
references/funder-fit-and-research-strategy.md — fit dimensions, funder types, multi-funder strategyreferences/proposal-structure-and-narrative.md — per-funder structures, narrative disciplinereferences/budget-design-and-justification.md — budget categories, indirect costs, common errorsresearch/litreview — literature review for proposalsc-level-advisor/general-counsel-advisor — legal review of termsc-level-advisor/cfo-advisor — financial reviewまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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".
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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."
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。