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 commands/arnwaldn/agent-owl/owl-auditgit clone --depth 1 https://github.com/arnwaldn/agent-owlWrote 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/commands/arnwaldn/agent-owl/owl-audit)<a href="https://agentmods.dev/commands/arnwaldn/agent-owl/owl-audit"><img src="https://agentmods.dev/badge/commands/arnwaldn/agent-owl/owl-audit.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 | $0.00010 | $0.00668 |
| Opus 5 | $0.00005 | $0.00334 |
| Sonnet 5 | $0.00002 | $0.00134 |
| Haiku 4.5 | $0.00001 | $0.00067 |
Grade A, and why
owl-audit 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 3d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Owl
Run file integrity and EU AI Act compliance operations via MCP tools. Supports multi-project operation — commands auto-detect the current project.
Operations
Parse the user's argument to determine which operation to run:
File Integrity
| Command | MCP Tool | Description |
|---|---|---|
scan |
audit_full_scan |
Full integrity scan of all watched paths |
verify <filepath> |
audit_verify_file |
Verify a single file's hash |
history <filepath> |
audit_file_history |
Show audit trail for a file |
stats |
audit_stats |
Show store statistics |
violations |
audit_violations |
List all integrity violations |
EU AI Act Compliance
| Command | MCP Tool | Description |
|---|---|---|
status <system> |
compliance_status |
Compliance overview for an AI system |
validate <system> |
compliance_validate |
SHACL validation (ontology constraints) |
annex-iv <system> |
compliance_annex_iv |
Annex IV documentation completeness |
report <system> [html|md] |
compliance_export_report |
Export formatted compliance report |
incidents [system] |
compliance_incidents |
List incidents (Art. 73) |
retention |
compliance_retention_check |
Check log retention (Art. 19) |
register <name> [risk_level] |
compliance_register_system |
Register new AI system |
Query
| Command | MCP Tool | Description |
|---|---|---|
sparql "<SPARQL query>" |
audit_sparql |
Execute read-only SPARQL query |
Project Management
| Command | MCP Tool | Description |
|---|---|---|
init [path] |
audit_init |
Initialize AO in a directory (default: CWD) |
projects |
audit_list_projects |
List all active AO projects in cache |
Instructions
- Parse the operation from the argument string
- Call the corresponding MCP tool from the
owl-auditserver - Format the result clearly for the user
- If no argument is provided, show a summary: call
audit_statsthen display available commands - For project-wide commands, pass
project_pathif the user specifies one
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.
- 3d ago First seen · 71 lines · 10 tokens per session scan A 74555c9b9a9a
owl-audit is a command published in the GitHub repository arnwaldn/agent-owl (0 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 668 once invoked, about $0.0001 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.
Other commands, from other repositories
evidence
Export a signed compliance evidence package as JSON or PDF for regulatory handoff.
comply
Run a full EU AI Act compliance scan on your Python AI project.
ai-act-scan
Scan a codebase for EU AI Act compliance evidence and gaps. Produces a dimension-scored report with per-file findings, architecture graph, and prioritized recommendations.
ai-act-article
Show which analyzers, compliance dimensions, and current findings in this codebase map to a specific EU AI Act article.
ai-act-scan-fix
Scan a codebase, then propose concrete remediation (code edits, new files, tests) for the top compliance gaps. Does NOT auto-apply — always shows the plan first.
report
Produce executive and technical compliance reports.