Grant Review

Community

neuromechanist

grant-review

This skill should be used when the user asks to "review a grant", "review my proposal", "score this grant", "evaluate my specific aims", "critique my research strategy", "review as an NIH reviewer", "review as an NSF panelist", "give me reviewer feedback", "check my grant proposal", "review my R01", "review my K99", "review my SBIR", "review my STTR", "review my Phase I application", "review my Phase II application", "review my commercialization plan", "evaluate my CAREER proposal", "run a mock study section", "run a grant readability review", "check my clear sentences", "review my resubmission", "review this PDF", "check my proposal PDF", "analyze my grant layout", or mentions grant review, proposal critique, NIH scoring, NSF panel review, small business grant review, study section feedback, or proposal PDF review.

Overview

Publisher	neuromechanist
Repository	`research-skills`
Skill name	`grant-review`
Stars	51
Forks	9
Bundled files	10
License	BSD-3-Clause
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
10 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by neuromechanist on GitHub. Read the source before you install it.

Installation

Install the Grant Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/neuromechanist/research-skills/tree/main/plugins/grant/skills/grant-review
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/neuromechanist/research-skills/tree/main/plugins/grant/skills/grant-review

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/neuromechanist/research-skills.git /tmp/research-skills
mkdir -p .claude/skills
cp -r /tmp/research-skills/plugins/grant/skills/grant-review .claude/skills/grant-review

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Grant Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Grant Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Grant Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.
Readability (run BEFORE the panel): one fresh-context reviewer restricted to clarity, with no merit scoring. Follow references/readability-procedure.md; a panel can run clean while the first page still contains prose the PI cannot follow on first read. The default pass reports line-anchored, length-neutral rewrites for long chained sentences, ambiguous pronouns, premature terms or abbreviations, rhetorical inversions, and gratuitous self-undermining while preserving substantive limitations. If requested, the same reviewer can add the optional conciseness hunt as a second pass; do not fan out a second agent unless the caller asks for it. Conciseness rewrites must be strictly shorter while preserving every number, citation, qualification, and required element.

Dispatch

Pick the branch for the current tool. Single and panel reviews follow references/review-procedure.md; readability reviews follow references/readability-procedure.md and never score merit.

Claude Code: Agent(subagent_type: "grant:grant-review", ...) passing the proposal path, mechanism, and mode. The agent selects the readability procedure when mode=readability; for panel mode, issue one Agent call per reviewer role in a single message so they run in parallel, then a final synthesis Agent call.
Codex CLI: plugin installation exposes this skill, not a Codex subagent. To use a fresh-context Codex reviewer, first copy agents/templates/grant-review.toml to ~/.codex/agents/ or .codex/agents/, then invoke that configured agent if the current Codex surface supports /agent. Pass mode=readability for the non-scoring pass. For panel mode, ensure max_threads covers 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.md reviewer in agents/templates/. Invoke that configured agent when the current Copilot surface supports custom agents; pass mode=readability for the non-scoring pass and use /fleet for panel mode when available. If running outside a plugin install, copy agents/templates/grant-review.agent.md to .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, else find . -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 follow references/readability-procedure.md for mode=readability, or references/review-procedure.md for other modes.

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/readability-procedure.md -- non-scoring first-read clarity pass with anchored, page-neutral rewrites and an optional concise-writing hunt.
references/nih-review-criteria.md, references/nih-career-training-criteria.md, references/nsf-review-criteria.md -- criteria and scoring.
references/sbir-sttr-review-criteria.md -- SBIR/STTR (R41, R42, R43, R44) criteria. These are not reviewed under the RPG Simplified Review Framework; they keep the five classic scored criteria plus commercial-potential questions, Commercialization Plan assessment, Phase I milestones, Phase I progress, and Fast-Track acceptability.
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 (invoke through the host's skill-invocation mechanism) -- AI-writing patterns to flag in grant prose.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Grant Review AI skill do?

Why use Grant Review on TypingMind?

Because you install it once and use it with any model. Grant Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Grant Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/neuromechanist/research-skills/tree/main/plugins/grant/skills/grant-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Grant Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Grant Review?

As many as you like. As long as a model supports skills, you can use Grant Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Grant Review AI skill free?

Yes. It is published on GitHub by neuromechanist under the BSD-3-Clause license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Grant Proposal Review

When to use

Why a fresh-context reviewer

Modes (user decides each run)

Dispatch

The brain (do not duplicate into dispatch or agent shells)

Bundled files

Frequently asked questions

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