CtrlK
BlogDocsLog inGet started
Tessl Logo

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.

62

Quality

73%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./scientific_writer/.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

71%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 body with strong progressive disclosure (verified one-level-deep references and assets, all present), a clearly sequenced phase workflow with timing anchors, and mostly concrete agency-specific facts. The main cost is token weight: the 25-item generic mistakes lists and the motivational closing note pad the file without adding knowledge Claude lacks.

Suggestions

Cut the "Common Mistakes to Avoid" section down to the genuinely agency-specific items (page limits, required sections, mission mismatch, mechanism fit) and move the generic writing mistakes into writing_principles.md, which already covers them.

Delete the "Final Note" paragraph and trim the overlap between "Integration with Other Skills" and the reference listing.

Add an explicit pre-submission compliance checklist (page limits per section, required forms, font/margin rules) to Phase 4/5 so the final validation checkpoint is concrete rather than "Proofread all materials".

DimensionReasoningScore

Conciseness

The agency overviews, phase workflow, and reference pointers carry real, non-obvious information (page limits, PAPPG 24-1, CM03 form, timeline offsets), but there is measurable padding: the 25-item "Common Mistakes to Avoid" section includes generic writing advice Claude already knows ("Poor Organization", "Excessive Jargon", "Verbosity", "Inconsistent Terminology"), and the closing "Final Note" ("Grant writing is both an art and a science...") is pure fluff. Not 4: multiple sections, not just minor instances, could be trimmed without losing anything Claude doesn't already know.

3 / 5

Actionability

Mostly concrete: exact page limits ("Specific Aims (1 page) + Research Strategy (12 pages for R01)", "15-page project description limit"), a copy-paste-ready command for figure generation ("python skills/scientific-schematics/scripts/generate_schematic.py ... --doc-type grant"), named forms (NSTC "CM03"), and a 5-phase schedule with dates relative to the deadline. Not 5: the deep how-to is delegated to references, and several sections (agency overviews, mistakes lists) describe rather than instruct, leaving minor gaps in what can be executed directly from SKILL.md.

4 / 5

Workflow Clarity

The "Workflow for Grant Development" gives a clear 5-phase sequence, each with activities, outputs, and an explicit time anchor ("2-6 months before deadline" through "1 week before deadline"), plus revision feedback loops in Phase 3 ("Revise based on feedback") and a verification checkpoint in Phase 5 ("Verify all documents and formatting", "Confirm successful submission"). Not 5: final compliance validation (e.g., page-limit checking) is implied by "Proofread all materials" rather than given as an explicit per-artifact checklist; not 3 because the sequence and most checkpoints are explicit.

4 / 5

Progressive Disclosure

The body is a genuine overview that pushes detail into 12 reference files and 3 asset templates, each cited by name with a one-line description of what it contains (e.g., "references/review_criteria.md: how NIH, NSF, DOE, and DARPA score proposals"); every referenced path was verified to exist in the bundle, and references cross-link only to sibling files at the same level (no 2+ level nesting). Not 4: structure and signaling of what lives where are clean, with only the unreferenced references/README.md as a trivial omission.

5 / 5

Total

16

/

20

Passed

Description

75%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 specific, well-scoped description that names concrete deliverables and a distinct multi-agency niche. Its main weakness is the absence of an explicit "Use when..." trigger clause, and it misses several natural trigger phrases ("grant proposal", "grant application", "R01", "specific aims").

Suggestions

Add an explicit trigger clause, e.g. "Use when writing grant proposals or responding to NSF, NIH, DOE, DARPA, or NSTC solicitations and funding announcements."

Include natural user phrasings such as "grant proposal", "grant application", "specific aims", and "R01" alongside the agency acronyms.

Keep the current third-person, comma-delimited component list — it is the description's strongest asset.

DimensionReasoningScore

Specificity

The description opens with a concrete action ("Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC") and then enumerates multiple specific deliverables — "Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements" — giving comprehensive coverage of the skill's scope. Not 4: coverage spans the full proposal-writing lifecycle rather than having a minor gap.

5 / 5

Completeness

The "what" is clear and concrete (writing proposals plus named components), but there is no "Use when..." clause or equivalent explicit trigger guidance — when to use it is only weakly implied by the domain itself. Per the judging guidelines, a missing 'Use when...' clause caps completeness at 3; not 4 because the 'when' is not explicit at all.

3 / 5

Trigger Term Quality

Strong natural keywords users would say: the agency acronyms (NSF, NIH, DOE, DARPA, NSTC), "research proposals", "broader impacts", "significance statements", "budget". Not 5: common user phrasings like "grant proposal", "grant application", "funding", or mechanism names like "R01" and "specific aims" are absent, so a few natural terms are missing.

4 / 5

Distinctiveness Conflict Risk

It carves out a clear niche (agency-specific research grant proposals for five named funders) with distinct triggers like agency acronyms and "broader impacts" that no adjacent skill (e.g., scientific writing) would claim. Not 4: overlap risk with generic writing skills is minimal because the agency names anchor the triggers.

5 / 5

Total

17

/

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

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.