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 agentmods add agents/sabbour/agentweaver/rai_policygit clone --depth 1 https://github.com/sabbour/agentweaverWrote 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/agents/sabbour/agentweaver/rai_policy)<a href="https://agentmods.dev/agents/sabbour/agentweaver/rai_policy"><img src="https://agentmods.dev/badge/agents/sabbour/agentweaver/rai_policy.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00321 |
| Opus 5 | $0.00000 | $0.00161 |
| Sonnet 5 | $0.00000 | $0.00064 |
| Haiku 4.5 | $0.00000 | $0.00032 |
Grade A, and why
rai_policy 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 yesterday.
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
RAI Policy
This policy defines the Responsible AI checks performed by the Rai agent on this project.
Check Categories
Critical (always enabled — cannot be disabled)
- Credential leaks — API keys, tokens, passwords, connection strings in code or content
- PII exposure — personal data (names, emails, phone numbers, IDs) without justification
- Injection vulnerabilities — prompt injection, SQL injection, command injection
- Harmful content — content that could cause physical or emotional harm
Advisory (enabled by default — can be disabled with justification)
- Exclusionary language — terms that exclude or demean groups of people
- Deceptive patterns — UI/UX patterns designed to mislead users
- Bias indicators — algorithmic or content bias in models or outputs
- Insufficient grounding — AI outputs presented as facts without citations
- Privacy risks — unnecessary data collection or retention in prompts
Terminology Standards
Use inclusive, precise language. Avoid: blacklist/whitelist (use allowlist/denylist), master/slave (use primary/replica), and gendered defaults.
Opt-Out
Advisory checks may be disabled temporarily with justification logged to .squad/rai/audit-trail.md. Critical checks cannot be disabled. Temporary opt-outs auto-expire after 30 days.
Audit Trail
All RAI review findings are recorded to .squad/rai/audit-trail.md. This file is append-only and is never edited after write.
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.
- yesterday First seen · 31 lines · 0 tokens per session scan A 90d45a6b841e
rai_policy is an agent published in the GitHub repository sabbour/agentweaver (5 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 321 tokens. 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 2026-09-03.
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