Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/raja21068/AutoResearchnpx agentmods add skills/raja21068/autoresearch/grant-proposalWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/raja21068/autoresearch/grant-proposal)<a href="https://agentmods.dev/skills/raja21068/autoresearch/grant-proposal"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/grant-proposal/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/raja21068/autoresearch/grant-proposal"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/grant-proposal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00131 | $0.08097 |
| Opus 5 | $0.00066 | $0.04049 |
| Sonnet 5 | $0.00026 | $0.01619 |
| Haiku 4.5 | $0.00013 | $0.00810 |
Grade A, and why
grant-proposal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to grant-proposal — 79 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 656 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grant Proposal: From Research Ideas to Fundable Application
Draft a grant proposal based on: $ARGUMENTS
Overview
This skill turns validated research ideas into a structured, reviewer-ready grant proposal. It chains sub-skills into a grant-specific pipeline:
/research-lit → /novelty-check → [structure design] → [draft] → /research-review → [revise] → GRANT_PROPOSAL.md
(survey) (verify gap) (aims + matrix) (prose) (panel review) (fix) (done!)
This is a parallel branch, not part of the linear Workflow 1→1.5→2→3 pipeline. After /idea-discovery produces validated ideas, the user can either:
- Go to
/experiment-bridge→/auto-review-loop→/paper-writing(implement & publish) - Go to
/grant-proposal(write funding application first, then implement after funding)
┌→ /experiment-bridge → /auto-review-loop → /paper-writing (publish track)
/idea-discovery ────┤
└→ /grant-proposal → [get funded] → /experiment-bridge → ... (funding track)
Grant proposals argue for future work (feasibility + potential), not completed work (results + claims). This skill handles the unique requirements of grant writing: narrative arc design, reviewer-facing structure, budget justification, timeline planning, and agency-specific formatting.
Constants
- GRANT_TYPE =
KAKENHI— Default grant type. Supported:KAKENHI,NSF,NSFC,ERC,DFG,SNSF,ARC,NWO,GENERIC. Override via argument (e.g.,/grant-proposal "topic — NSF"). - GRANT_SUBTYPE =
auto— Sub-type within the grant agency. Examples: KAKENHIStart-up/Wakate/Kiban-B; NSFCYouth/Excellent-Youth/Distinguished/Overseas/Key; NSFCAREER/CRII/Standard. Auto-detected from argument or defaults to the most common sub-type. - REVIEWER_MODEL =
gpt-5.4— Model used via Codex MCP for proposal review. Must be an OpenAI model (e.g.,gpt-5.4,o3,gpt-4o). - OUTPUT_FORMAT =
markdown— Output format. Supported:markdown,latex. LaTeX uses grant-specific templates when available. - MAX_REVIEW_ROUNDS = 2 — Maximum external review-revise cycles before finalizing.
- OUTPUT_DIR =
grant-proposal/— Directory for generated proposal files. - LANGUAGE =
auto— Output language. Auto-detected from grant type: KAKENHI→Japanese, NSF→English, NSFC→Chinese, ERC→English, DFG→English (or German), SNSF→English, ARC→English, NWO→English. Override explicitly if needed. - AUTO_PROCEED = false — At each checkpoint, always wait for explicit user confirmation before proceeding. Grant proposals require PI-specific judgment at every stage. Set
trueonly if user explicitly requests fully autonomous mode.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 656 lines · 131 tokens per session scan A d7d03a7e0941
grant-proposal is a skill published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 131 tokens to every session and 8,097 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to grant-proposal, differing in 79 lines, and is treated as a copy.
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