Borrowing it
Nothing to install: this file belongs to alohays/paper2pr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alohays/paper2pr/main/.claude/skills/deep-audit/SKILL.mdgit clone --depth 1 https://github.com/alohays/paper2prWrote 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/alohays/paper2pr/deep-audit)<a href="https://agentmods.dev/skills/alohays/paper2pr/deep-audit"><img src="https://agentmods.dev/badge/skills/alohays/paper2pr/deep-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/alohays/paper2pr/deep-audit"><img src="https://agentmods.dev/badge/skills/alohays/paper2pr/deep-audit.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 | $0.00076 | $0.01499 |
| Opus 5.5 | $0.00030 | $0.00600 |
| Sonnet 5.5 | $0.00015 | $0.00300 |
| Haiku 4.5 | $0.00008 | $0.00150 |
Grade A, and why
deep-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 1mo 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/deep-audit — Repository Infrastructure Audit
Run a comprehensive consistency audit across the entire repository, fix all issues found, and loop until clean.
When to Use
- After broad changes (new skills, rules, hooks, scripts, AGENTS.md edits)
- Before releases or major commits
- When the user asks to "find inconsistencies", "audit", or "check everything"
Workflow
PHASE 1: Launch 4 Parallel Audit Agents
Launch these 4 agents simultaneously using Agent with subagent_type=general-purpose:
Agent 1: Canonical Docs Accuracy
Focus: AGENTS.md (the single canonical description) and README.md (short external intro)
- All numeric claims match reality (skill count, agent count, rule count, hook count, script count)
- All file paths mentioned actually exist on disk
- All skill/agent/rule/script names match actual directory and file names
- Code examples and commands are correct (
scripts/deckpath.py,scripts/deckprofile.py,scripts/new_deck.pyflags exist) - Cross-references resolve
- No stale counts, and no mentions of layers that git history shows as removed
Agent 2: Hook Code Quality
Focus: .claude/hooks/*.py and .claude/hooks/*.sh
- No remaining
/tmp/usage (should use~/.claude/sessions/) - Hash length consistency (
[:8]across all hooks) - Proper error handling (fail-open pattern: top-level
try/exceptwithsys.exit(0)) - JSON input/output correctness (stdin for input, stdout/stderr for output)
- Exit code correctness (0 for non-blocking, non-zero only when intentionally blocking)
from __future__ import annotationsfor Python 3.8+ compatibility- Correct field names from hook input schema (
sourcenottypefor SessionStart) - PreCompact hooks print to stderr (stdout is ignored)
Agent 3: Skills, Agents, and Rules Consistency
Focus: .claude/skills/*/SKILL.md, .claude/agents/*.md, .claude/rules/*.md, .claude/rules/slide-profiles/*.yml
- Valid YAML frontmatter in all files
- No stale
disable-model-invocation: true allowed-toolsvalues are sensible- Rule
paths:reference existing directories - No contradictions between rules, or between a rule and the profile numbers the gate enforces
- AGENTS.md skills and agents tables match actual directories 1:1
- Every agent a skill launches exists in
.claude/agents/ - All templates referenced in rules/skills exist in
templates/
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.
- 1mo ago First seen · 135 lines · 76 tokens per session scan A ffd62148be2a
deep-audit is a skill published in the GitHub repository alohays/paper2pr (6 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 1,499 once invoked, about $0.0003 per session on Opus 5.5. 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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