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 strikersam/autonomous-ai-agency --skill system-prompt-auditgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/strikersam/autonomous-ai-agency/system-prompt-audit)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/system-prompt-audit"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/system-prompt-audit/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/strikersam/autonomous-ai-agency/system-prompt-audit"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/system-prompt-audit.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 | $0.00000 | $0.00602 |
| Opus 5 | $0.00000 | $0.00301 |
| Sonnet 5 | $0.00000 | $0.00120 |
| Haiku 4.5 | $0.00000 | $0.00060 |
Grade A, and why
system-prompt-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 12d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: system-prompt-audit
Purpose
Audit all system-level instructions embedded in this repository's Claude configuration, surface them as a structured inventory, and validate them for consistency, safety, and alignment with project goals.
Inspired by CL4R1T4S (Latin: "clarity") — the open-source project that collects and publishes AI system prompts to promote transparency.
When to Use
- Run before merging changes to
.claude/directory - Run as part of release readiness checks
- Run when a new agent or skill is added
- Run on-demand for governance audits
Steps
1. Inventory Collection
Scan the following paths:
.claude/agents/ → agent persona definitions
.claude/skills/ → skill behavioral specs
.claude/commands/ → command implementations
CLAUDE.md → root-level project instructions
For each file, record:
- File path
- Word count (proxy for complexity)
- Presence of: role definition, constraints, examples, output format
2. Consistency Check
Cross-reference all files for:
- Duplicate roles: two agents claiming the same responsibility
- Contradictory constraints: one skill allows X, another forbids X
- Missing output formats: skills that don't specify what they produce
- Undocumented side effects: skills that write files/commit without stating so
3. Safety Check
Flag any instructions that:
- Allow unrestricted file system writes
- Allow network calls without validation
- Grant escalated permissions
- Lack human-in-the-loop checkpoints for destructive operations
4. Generate Audit Report
Write docs/system-prompt-audit.md with:
# System Prompt Audit Report
Generated: <timestamp>
## Summary
- Total components audited: N
- Agents: N | Skills: N | Commands: N
- Issues found: N (critical: N, warnings: N, info: N)
## Inventory Table
| Component | Type | Role | Has Constraints | Has Examples |
|-----------|------|------|-----------------|--------------|
## Issues
### Critical
...
### Warnings
...
### Info
...
## Full Behavioral Inventory
[per-component breakdown]
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.
- 12d ago First seen · 90 lines · 0 tokens per session scan A 5b65c2715ed7
system-prompt-audit is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 602 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 2026-08-31.
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