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research-grants

Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.

57

Quality

64%

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./.claude/skills/research-grants/SKILL.md

The canonical home for this skill is research-grants in K-Dense-AI/scientific-agent-skills

SKILL.md
Quality
Evals
Security

Quality

Content

60%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 well-structured overview skill with a genuinely useful phased workflow and a clean, verified one-level-deep reference bundle. Its weaknesses are verbosity in sections that restate common knowledge, and actionability that leans on pointers to references rather than carrying executable detail in the body.

Suggestions

Cut or collapse the ~45-line 'Common Mistakes' section to a short pointer list — most entries (avoid jargon, don't exceed page limits, submit on time) are knowledge Claude already has and belong in references/writing_principles.md if anywhere.

Delete or trim the 'Final Note' paragraph and the motivational lines; replace with one or two non-obvious operational facts (e.g., the 48-hour-early submission rule already appears in Phase 5).

Move the duplicated Agency-Specific Overview detail into the existing per-agency reference files, keeping only a comparison table (agency / review criteria / page limits / required sections) in the body, and add the missing pointer to references/README.md.

DimensionReasoningScore

Conciseness

Mostly efficient, but the 'Common Mistakes' section spends ~45 lines on knowledge Claude already has ("Excessive Jargon: Inaccessible to broader review panel", "Verbosity: Unnecessarily complex or wordy writing", "Exceeding Page Limits: Automatic rejection"), and the 'Final Note' is motivational padding ("Grant writing is both an art and a science... persistence and revision are key"). Not a 2 because the agency overviews, workflow, and reference pointers do carry non-obvious, load-bearing specifics (page limits, PAPPG 24-1, bilingual NSTC abstracts).

3 / 5

Actionability

Concrete specifics exist — the executable scientific-schematics command, "15-page project description limit (includes Results from Prior NSF Support, max 5 pages)", "Specific Aims (1 page) + Research Strategy (12 pages for R01)", "Submit 24-48 hours before deadline" — but the actual writing guidance is deferred to references, and most workflow steps are high-level directions ("Write specific aims or objectives", "Develop project description/research strategy") without executable detail in the body. Not a 4 because the body itself instructs more than it equips; the operative detail lives one file away.

3 / 5

Workflow Clarity

The five-phase workflow (Planning → Drafting → Internal Review → Finalization → Submission) is clearly sequenced with timeline anchors, per-phase Activities and Outputs, and real checkpoints: mock review in Phase 3, "Verify all documents and formatting" and "Confirm successful submission" in Phase 5. Not a 5 because validation is advisory rather than a feedback loop — no explicit 'if verification fails, fix and re-verify' step, and the "Critical Tip" about portal crashes is a warning rather than a checkpoint.

4 / 5

Progressive Disclosure

Verified against the actual bundle: all 12 references/ and 3 assets/ files cited in the body exist, are one level deep, and are clearly signaled (Core Components, Review Criteria, Writing Principles, Proposal Types sections plus a Resources section and a Templates section). Not a 5 because the Agency-Specific Overview duplicates content that belongs in the per-agency reference files (nsf_guidelines.md, nih_guidelines.md, etc.), and references/README.md exists in the bundle but is never linked from the body.

4 / 5

Total

14

/

20

Passed

Description

70%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.

A strong, specific description with excellent distinctiveness and good trigger coverage, undermined by the complete absence of a 'Use when...' clause and the miss of the most natural keyword ('grant'). The what is unambiguous; the when is left entirely to inference.

Suggestions

Append an explicit trigger clause, e.g. "Use when writing or revising grant proposals, specific aims pages, budget justifications, or broader impacts sections, or when responding to a solicitation, BAA, or reviewer summary statement."

Add the natural keywords users actually say — "grant", "grant writing", "grant proposal", "funding proposal" — none of which currently appear in the description.

Convert the trailing noun-phrase list into verbs ("formats proposals to agency requirements, prepares budgets and justifications, drafts broader impacts and significance statements") so each listed item is a concrete action.

DimensionReasoningScore

Specificity

The description opens with a concrete action ("Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC") and lists several specific facets: "Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements". Not a 5 because the latter items are noun phrases rather than concrete actions — it never says what it does with 'review criteria' or 'broader impacts' (write them? evaluate them?).

4 / 5

Completeness

The 'what' is clear and concrete, but there is no 'Use when...' clause or equivalent explicit trigger guidance anywhere in the description — per the judging guidelines this caps completeness at 3. Not a 2 because the 'what' is far from vague, and not a 4 because 'when' is entirely absent rather than merely implicit.

3 / 5

Trigger Term Quality

Strong agency-name triggers ("NSF, NIH, DOE, DARPA, and Taiwan NSTC") plus natural phrases like "research proposals" and "budget preparation". Not a 5 because the most natural user phrasings — "grant", "grant writing", "grant proposal", "funding proposal" — are absent; a user asking for help with a 'grant application' would not textually match this description, and mechanism terms like 'R01' or 'specific aims' are missing too.

4 / 5

Distinctiveness Conflict Risk

The agency names (NSF, NIH, DOE, DARPA, NSTC) carve out a clear niche with distinct triggers; no other plausible skill in a scientific-skills library would collide with 'write research proposals for these five agencies'. Conflict risk is minimal.

5 / 5

Total

16

/

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
K-Dense-AI/claude-scientific-writer
Reviewed

Table of Contents

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