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grants

NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.

77

Quality

97%

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Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strongly engineered workflow document: executable commands throughout, explicit sequencing with stop conditions, validation, error-recovery loops, and a clean overview-plus-references structure. The only weakness is minor non-essential content — a hardcoded time-sensitive receipt-date table and maintainer-facing build provenance — that costs some token efficiency.

Suggestions

Move the submission receipt-date table into a reference file (or add a 'verify current dates at grants.nih.gov' instruction) — hardcoded dates like 'Feb 5, Jun 5, Oct 5' are time-sensitive and will silently drift out of accuracy.

Trim the build-provenance footer ('Source spec ... gitignored', 'Build pattern: Path B', 'PR #657 audit') from the body — it is maintainer metadata that consumes agent context without operational value.

Replace the hardcoded fiscal_years example array '[2023, 2024, 2025, 2026]' in the curl templates with a placeholder pointing to the fiscal_year_calculator.py output, so the copy-paste commands cannot be run with stale years.

DimensionReasoningScore

Conciseness

The body is largely lean — no explanations of concepts Claude already knows (no 'what is NIH' or library tutorials), and the intake questions, curl templates, and tables are all operational content. Minor trimmable material remains: the hardcoded submission receipt dates ('Feb 5, Jun 5, Oct 5' etc.) are time-sensitive and not in a deprecated/verification section, and the build-provenance footer ('Source spec ... gitignored, not present', 'PR #657 audit', 'Path B (direct conversion)') is maintainer noise irrelevant to the executing agent. This fits anchor 4 ('Efficient; minor instances ... that could be trimmed') better than anchor 5, and better than anchor 3, which requires more substantial unnecessary explanation.

4 / 5

Actionability

Guidance is fully executable: complete copy-paste curl POST commands with full JSON payloads for both narrow (AND) and broad (OR) RePORTER searches, exact script invocations with flags ('python scripts/mechanism_matcher.py --career-stage "early_career" --prelim-data "pilot" ...'), literal intake question scripts with option lists, the NOSI URL pattern, and a runnable docx validation command ('python3 -c "import zipfile,sys; zipfile.ZipFile(sys.argv[1]).testzip()"'). This matches the score-5 anchor (copy-paste ready, common cases covered) rather than anchor 4, which allows minor gaps — placeholders like <research idea> are the only substitutions needed.

5 / 5

Workflow Clarity

The workflow is clearly sequenced Phase 1 (intake with a hard stop condition: 'After Q6, commit and start Phase 2A. Never re-open intake') → Phase 2A/2B → Phase 3 → Phase 4, with explicit validation in Phase 4 (zip-integrity check plus confirming required sections are present), feedback loops (retry once after 3s; after 3 consecutive failures stop and alert; 'Consensus returns 0 for a facet → surface explicitly'), and a checklist-style Anti-Patterns section. This matches the score-5 anchor (explicit validation steps, error-recovery feedback loops, checklists) rather than anchor 4, which permits minor validation gaps.

5 / 5

Progressive Disclosure

The body is a genuine overview that splits detail into three one-level-deep, well-signaled reference files (references/reporter_post_patterns.md, references/nih_mechanism_matching.md, references/docx_9_sections.md — all verified to exist), linked both inline and in a dedicated '## References' section, plus a '## Tooling' table for the three scripts. The full DOCX spec and mechanism matrix live in references while only summaries stay inline. This matches the score-5 anchor (clear overview, well-signaled one-level-deep references, appropriate split) rather than anchor 4, which expects minor organization gaps.

5 / 5

Total

19

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: concrete third-person capability statements, an explicit 'Use when' clause with five natural trigger phrases, and an explicit scope boundary that reduces conflict risk. The only mild critique is length (~160 words), but every clause carries capability or trigger information, so no dimension is penalized for padding.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions with comprehensive coverage: 'Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets)', 'Runs a 5-facet Consensus positioning analysis', 'maps the research to the right NIH institutes and study sections via RePORTER', 'finds NOSIs and funded overlap', 'produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation'. This matches the score-5 anchor ('Lists multiple specific concrete actions; comprehensive coverage') and exceeds anchor 4, which is for coverage with minor gaps — no capability area of the workflow is missing.

5 / 5

Completeness

Both 'what' and 'when' are answered explicitly and concretely. The 'what' is a detailed capability list (intake, positioning analysis, institute mapping, NOSI discovery, docx deliverable), and the 'when' is a full 'Use when...' clause with five concrete trigger phrases. This matches the score-5 anchor exactly ('Clearly and explicitly answers both what AND when with concrete trigger phrases'); it is not anchor 4, where the 'when' is present but could be more explicit or specific.

5 / 5

Trigger Term Quality

Trigger coverage is comprehensive with natural user phrasings and synonyms: 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research', plus the general 'research funding' and 'any grant-related request'. This matches the score-5 anchor (comprehensive natural terms including synonyms) rather than anchor 4 ('a few natural terms missing') because the example phrases span the realistic ways a user would ask for grant discovery; terms like 'grant writing' are absent but describe a different task outside this skill's purpose.

5 / 5

Distinctiveness Conflict Risk

The skill occupies a clear NIH-grant-discovery niche with distinct triggers and an explicit scope boundary: 'NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.' This actively prevents mis-triggering on general funding or literature-search requests, matching the score-5 anchor (clear niche with distinct triggers; minimal conflict risk) rather than anchor 4, which allows minor overlap risk with closely related skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

alirezarezvani/claude-skills

Path

research/grants/skills/grants/SKILL.md

Reviewed

Table of Contents

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