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 rhein1/agoragentic-integrations --skill agoragentic-governgit clone --depth 1 https://github.com/rhein1/agoragentic-integrationsWrote 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/rhein1/agoragentic-integrations/agoragentic-govern)<a href="https://agentmods.dev/skills/rhein1/agoragentic-integrations/agoragentic-govern"><img src="https://agentmods.dev/badge/skills/rhein1/agoragentic-integrations/agoragentic-govern/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/rhein1/agoragentic-integrations/agoragentic-govern"><img src="https://agentmods.dev/badge/skills/rhein1/agoragentic-integrations/agoragentic-govern.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00247 |
| Opus 5 | $0.00021 | $0.00123 |
| Sonnet 5 | $0.00008 | $0.00049 |
| Haiku 4.5 | $0.00004 | $0.00025 |
Grade A, and why
agoragentic-govern 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 10d 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.
What it actually says
Agoragentic Govern
Use this skill when an action may edit, spend, publish, deploy, message, mutate trust, or otherwise create side effects.
- Classify the intended action and side effects.
- Resolve the applicable local policy/profile.
- Decide allow, ask, deny, or blocked from existing policy; do not invent authority.
- When approval is required, produce an owner-readable approval packet before execution.
- Record the policy decision and evidence references using local Harness/ECF artifacts.
- Fail closed when required policy, identity, cost, or evidence is missing.
Local governance artifacts do not grant hosted runtime, wallet, settlement, publication, trust, or ranking authority.
Advanced Context
- Micro ECF local policy: https://github.com/rhein1/agoragentic-integrations/tree/main/micro-ecf
- Harness Core evidence contracts: https://github.com/rhein1/agoragentic-harness-core
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.
- 10d ago First seen · 23 lines · 42 tokens per session scan A c8dbd07af6f8
agoragentic-govern is a skill published in the GitHub repository rhein1/agoragentic-integrations (36 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 247 once invoked, about $0.0002 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 2026-08-30.
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