Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ddanntheman/GrantForge --skill grant-draftgit clone --depth 1 https://github.com/ddanntheman/GrantForgeWrote 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/ddanntheman/grantforge/grant-draft)<a href="https://agentmods.dev/skills/ddanntheman/grantforge/grant-draft"><img src="https://agentmods.dev/badge/skills/ddanntheman/grantforge/grant-draft/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/ddanntheman/grantforge/grant-draft"><img src="https://agentmods.dev/badge/skills/ddanntheman/grantforge/grant-draft.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 | $0.00076 | $0.00948 |
| Opus 5.5 | $0.00030 | $0.00379 |
| Sonnet 5.5 | $0.00015 | $0.00190 |
| Haiku 4.5 | $0.00008 | $0.00095 |
Grade A, and why
grant-draft 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grant Draft
Write narrative that a reviewer scores highly and a skeptic cannot identify as machine-written. Draft section by section, never the whole application in one pass.
Before writing
Read, in order: the requirements matrix (requirements.md), the research
files (research/evidence.md, research/funder.md), the org profile
(.grantforge/profile/organization.md), the voice profile
(profile/voice.md if present), relevant boilerplate
(profile/boilerplate/), and the house-style skill. If research files are
missing, run grant-research first — drafting without an evidence base
produces assertions, not arguments.
Section discipline
For each narrative section in the requirements matrix:
- Answer the verbatim prompt. Reviewers score against their question, not against what the writer wished they had asked. Open the section by directly addressing the prompt's core ask; never open with org history unless the prompt asks for it.
- Respect the limit with headroom. Draft to ~95% of the word/page/ character limit. Report the count to the user with every draft. For portal submissions, count characters the way portals do (spaces included, unless the funder says otherwise).
- Load-bearing evidence. Every claim of need or effectiveness cites an
entry from
research/evidence.md. Every capability claim traces to the org profile. Nothing invented, ever. Missing support becomes a question to the user, asked before drafting continues. - Mirror the rubric. Where the funder published scoring criteria, check the draft covers every scored element, weighted roughly by points.
- Adapt boilerplate, never paste it. The answer library provides raw material; rewrite it to this funder's vocabulary, this project's facts, and this prompt's angle.
Standard section craft
- Need/problem statement: local data first, national context second, one to two sentences of human texture. End with the gap this project fills — not with a pitch.
- Project description: what, who, where, when, how many, delivered by whom. Activities map visibly to objectives; objectives are measurable and time-bound (SMART without using the acronym).
- Goals/objectives/outcomes: distinguish outputs (what the org does) from outcomes (what changes). Give each objective a target, a measure, and a data source.
- Evaluation plan: who collects what data, with what instrument, on what schedule, and how findings feed back into the program. Name an evaluator if the budget includes one.
- Organizational capacity: prove it with track record, named staff qualifications, and financial stewardship facts (clean audits, past federal awards managed) — not adjectives.
- Sustainability: name realistic funding continuation paths; funders read "we will seek other grants" as no plan.
- Timeline/logic model: build as a table or exhibit when allowed; offer a logic model whenever the funder is federal or education-sector.
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.
- 1mo ago First seen · 91 lines · 76 tokens per session scan A d4a8b8ef647b
grant-draft is a skill published in the GitHub repository ddanntheman/GrantForge (2 stars, last pushed 3mo ago), licensed MIT. It adds 76 tokens to every session and 948 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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live-preview
Mid-build visual verification loop. Takes screenshots of components during construction, not just after. Catches visual regressions and invisible features before they compound. Requires Playwright or similar screenshot tool.