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 jason21wc/ai-governance-mcp --skill start-projectgit clone --depth 1 https://github.com/jason21wc/ai-governance-mcpWrote 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/jason21wc/ai-governance-mcp/start-project)<a href="https://agentmods.dev/skills/jason21wc/ai-governance-mcp/start-project"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/start-project/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/jason21wc/ai-governance-mcp/start-project"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/start-project.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 | $0.00154 | $0.00778 |
| Opus 5 | $0.00077 | $0.00389 |
| Sonnet 5 | $0.00031 | $0.00156 |
| Haiku 4.5 | $0.00015 | $0.00078 |
Grade A, and why
start-project 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 11d 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 — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Runtime Context
After the skill loads, inspect the current directory, governance-memory markers, and Git state with ordinary read-only calls. Missing memory and missing Git history are expected greenfield states, not failures.
Instructions
You are onboarding a project so the work runs under the AI-governance framework from the start. The discriminating move is discovery before commitment: establish the founding context (Goal / Done-looks-like / Non-goals / app-vs-document) BEFORE any implementation, then lay down the governance + memory scaffolding. Read procedure.md in this skill folder for the full protocol; this is the orchestration shell.
Quick Start
- Collect the Runtime Context above, then govern —
evaluate_governance(planned_action="initialize and onboard a new project"). - Read
procedure.mdand run its phases in order: govern → calibrate (mode + app-vs-document) → minimal founding questions (CFR §1.3.5 floor, depth-scaled) →scaffold_project(preview → confirm; non-destructive gap-fill) → seed the design doc → hand off to plan-mode. - NEW mode only in this version. If the folder already has governance memory, confirm with the user before re-scaffolding (scaffold_project is non-destructive, but don't surprise them).
Key Principles
- The founding floor is non-negotiable (CFR §1.3.5). Even on a "clear" request, ask Goal / Done-looks-like / Non-goals / app-vs-document. Depth scales with calibration; the floor does not.
- App vs. document drives templates + loaders, not memory location. Memory files live in
_ai-context/for BOTH types (unified layout v2.62.0);project_type="code"adds root loaders (AGENTS.md/CLAUDE.md) pointing in and coding-flavored templates. Decide this before scaffolding. - Non-destructive.
scaffold_projectskips existing files — it fills gaps, never overwrites. Always run the preview (noconfirmed) → confirm (confirmed=true) flow. - Freeform, not a menu. Ask the founding questions as natural conversation, not an Option-A/B/C list (Behavioral Floor
freeform-dialogue).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 35 lines · 154 tokens per session scan A f16212f98c66
start-project is a skill published in the GitHub repository jason21wc/ai-governance-mcp (0 stars, last pushed 10d ago), licensed Apache-2.0. It adds 154 tokens to every session and 778 once invoked, about $0.0008 per session on Opus 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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