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/jeffrigby/somepulp-agents/deep-auditgit clone --depth 1 https://github.com/jeffrigby/somepulp-agentsWrote 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/jeffrigby/somepulp-agents/deep-audit)<a href="https://agentmods.dev/commands/jeffrigby/somepulp-agents/deep-audit"><img src="https://agentmods.dev/badge/commands/jeffrigby/somepulp-agents/deep-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 | $0.02032 |
| Opus 5 | $0.00005 | $0.01016 |
| Sonnet 5 | $0.00002 | $0.00406 |
| Haiku 4.5 | $0.00001 | $0.00203 |
Grade A, and why
deep-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Audit (Orchestrator)
Run a comprehensive, on-demand codebase audit by inspecting the project, deciding which specialist agents apply, launching them, and aggregating their findings into a single dated report.
This is resource-intensive and should only run when explicitly requested. For quick checks on recent changes, just ask Claude to review the diff.
Aspects requested (optional): "$ARGUMENTS"
Audit Aspects
- security →
security-auditor(secrets, injection, XSS, weak crypto, CVEs) - perf →
performance-analyzer(algorithms, N+1, async, memory, bundles) - deps →
library-modernizer(custom code → mature lib, deprecated APIs,@typesduplication) - quality →
code-quality-reviewer(smells, complexity, duplication, error handling) - dead →
dead-code-cleanupin detect-only mode (unused imports/exports/files/deps, with verification) - all → run every applicable specialist (default if no aspects given)
The launch mode is parallel by default — /deep-audit produces a batch report, so there's no reason to wait. All selected specialists are launched at once via a single message with multiple Agent calls. Append the literal token sequential to fall back to one-at-a-time execution (useful when debugging a specialist or when a transcript is easier to read serially).
Workflow
1. Parse arguments
Split $ARGUMENTS on whitespace. Tokens that match an aspect (security, perf, deps, quality, dead, all) select that specialist. The token sequential switches launch mode to one-at-a-time. Anything else is treated as a free-form scope hint to pass into each specialist (e.g., a path, glob, or "src/api only").
If no aspects are given, treat it as all.
2. Pre-analysis (orchestrator does this directly)
Read the project skeleton so each specialist gets a useful brief:
- Tech stack: presence of
package.json,tsconfig.json,requirements.txt,pyproject.toml,go.mod,Cargo.toml, etc. - Project conventions: read
CLAUDE.mdand top-levelREADME.mdif present. - Existing baselines: if a lint/typecheck script exists in
package.json, run it once and capture errors as a baseline (don't re-flag those). - Inventory: a Glob count of code files by extension to gauge audit size.
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 · 188 lines · 10 tokens per session scan A f3d3123c0fac
deep-audit is a command published in the GitHub repository jeffrigby/somepulp-agents (7 stars, last pushed 2mo ago), licensed MIT. It adds 10 tokens to every session and 2,032 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
audit
Run one selected Whats.Going.On. reviewer, or all selected reviewers in dependency waves.
operationalize
Turn an approved synthesis into explicitly untested, source-linked operator aids without executing procedures or changing systems.
cost
Produce a reconciled API-equivalent cost estimate for a completed Whats.Going.On. audit.
summarize
Reconcile completed Whats.Going.On. reviewers and create decision-grade audience reports.
upload
Verify a completed public WGO audit and open a draft PR in the configured report repository.
audit
Full project audit with Health Score, findings, and a prioritized fix plan.