Install
$ agentstack add skill-neuromechanist-research-skills-grant-review ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Grant Proposal Review
Routes a grant proposal to an independent, fresh-context reviewer that scores it against the official NIH or NSF criteria and returns a structured review. This skill is a thin dispatcher: it decides how to run the reviewer and in which mode. The review procedure, criteria, scoring rubrics, and output templates all live in references/ and are loaded by the reviewer, not duplicated here.
When to use
Activate when the user wants feedback on a grant proposal (specific aims, research strategy, project description) evaluated against NIH or NSF review criteria.
Why a fresh-context reviewer
Review validity depends on independence: a reviewer that shares the conversation that produced the proposal is biased toward it. Run the reviewer in a separate context and pass only framing (proposal path, mechanism/agency, resubmission status, target program), never the authoring rationale. This is also why the reviewer is a subagent on tools that support one, and an inline procedure where they do not.
Modes (user decides each run)
- Single (default): one independent reviewer applies the full procedure end to end.
- Panel (opt-in): spawn N independent reviewers in parallel, then a synthesis pass. Trigger on "mock study section", "panel review", or an explicit request for multiple reviewers. NIH: 3 reviewers; NSF: 2-3 panelists. Each reviewer scores independently from
references/; a final chair pass reconciles them into one output. Surface genuine disagreement rather than blindly averaging scores.
Dispatch
Pick the branch for the current tool. In every branch the reviewer follows references/review-procedure.md.
- Claude Code:
Task(subagent_type: "grant-review", ...)passing the proposal path, mechanism, and mode. For panel mode, launch oneTaskper reviewer role in parallel, then a final synthesisTask. - Codex CLI: plugin installation exposes this skill, not a Codex subagent. To use a fresh-context Codex reviewer, first copy
agents/templates/grant-review.tomlto~/.codex/agents/or.codex/agents/, then invoke that configured agent if the current Codex surface supports/agent. For panel mode, ensuremax_threadscovers the reviewer count. If no Codex subagent is configured or available, use the fallback branch. - Copilot CLI: plugin installation exposes this skill and, through
.github/plugin/plugin.json, the.agent.mdreviewer inagents/templates/. Invoke that configured agent when the current Copilot surface supports custom agents; use/fleetfor panel mode when available. If running outside a plugin install, copyagents/templates/grant-review.agent.mdto.github/agents/or~/.copilot/agents/. If no custom agent is available, use the fallback branch. - Fallback (no subagent support, or the user wants an interactive in-thread review): first locate the rubric (
$CLAUDE_PLUGIN_ROOT/skills/grant-review/references, elsefind . -type d -path '*/skills/grant-review/references' | head -1); if it cannot be found, stop and tell the user to install the grant plugin rather than reviewing from memory. Then followreferences/review-procedure.mddirectly in this context.
The brain (do not duplicate into dispatch or agent shells)
references/review-procedure.md-- step-by-step procedure: mechanism ID, ingest, score, synthesize, output.references/nih-review-criteria.md,references/nih-career-training-criteria.md,references/nsf-review-criteria.md-- criteria and scoring.references/review-best-practices.md-- calibration and common reviewer comments.references/review-output-templates.md-- NIH and NSF output format.examples/sample-nih-r01-review.md-- worked review;examples/sample-r01-aims.md-- sample proposal input for testing.- Sister skill
manuscript:humanizer-- AI-writing patterns to flag in grant prose.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: neuromechanist
- Source: neuromechanist/research-skills
- License: BSD-3-Clause
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.