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 xcaeser/work-skill --skill work-auditgit clone --depth 1 https://github.com/xcaeser/work-skillWrote 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/xcaeser/work-skill/work-audit)<a href="https://agentmods.dev/skills/xcaeser/work-skill/work-audit"><img src="https://agentmods.dev/badge/skills/xcaeser/work-skill/work-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/xcaeser/work-skill/work-audit"><img src="https://agentmods.dev/badge/skills/xcaeser/work-skill/work-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 | $0.00063 | $0.01228 |
| Opus 5.5 | $0.00025 | $0.00491 |
| Sonnet 5.5 | $0.00013 | $0.00246 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
work-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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Work / 7. Audit
Audit without changing source files. Keep the parent orchestrator accountable for scope, verification, decisions, and any later edits.
Apply reliability, restraint, simplicity, meaningful testing, user-state safety, and proof over status. Never preserve backwards compatibility; update current consumers and remove obsolete paths. Treat concrete evidence as the handoff requirement.
Fixed route
- If the exact subagent model, effort, or goal tools are unavailable, return
blockedwith the missing capability. Do not substitute a model or perform the audit in the parent. - Launch exactly one
gpt-5.6-solsubagent atxhigheffort withfork_turns: none. - Give it a fun call sign and a complete read-only task packet: exact task statement, ownership, source of truth, risk axes, exclusions, acceptance checks, and validation requirements.
- Keep early hypotheses independent and require concrete locations, reproductions, traces, or commands; reject status reports and unsupported “routine” conclusions.
- Require it to call
create_goalwith the exact audit goal before inspection andupdate_goal completeonly after the required checks pass. - Let the analyst run until it returns findings, a real blocker, or a user-input request. Do not cancel it because a polling window or arbitrary wall-clock interval elapsed; a wait timeout is not a failure.
- The analyst must not edit, commit, deploy, spawn, or delegate.
- Scale depth to the target and risk. Inspect only relevant paths, direct consumers, and evidence needed to verify findings; return the audit without process narration and stop when every material risk axis has a supported disposition.
- Report the successful launch as a compact table with
Agent,Working on,Goal,Ownership, andModel.
Work / 7. Audit
- Resolve the target: working tree, commit, branch comparison, artifact, runtime flow, or named files.
- Identify the source of truth and material risk axes: correctness, regressions, security, data loss, accessibility, performance, or missing validation.
- Before recommending tests, inspect the implementation, existing tests, public APIs, and actual user flows. Add test findings only for observed contracts, real regressions, or meaningful boundaries.
- Inspect independently and collect concrete evidence, exact locations, and the smallest credible reproduction.
- Challenge the happy path and the exact contract at the boundaries the task can affect: malformed input, offline or hanging work, retries, partial state, interruption, permissions, upgrades, and recovery.
- Check the architecture against the simplest complete implementation, modular concerns, existing dependencies and their documentation/types, and long-term decisions rather than stopgaps.
- Reject style preferences, unsupported suspicion, findings without material impact, and reductions that merely restate the original problem.
- Verify the handoff in the parent; an analyst summary is not proof. If the route is blocked, record the exact gap and do not keep repeating it without a materially new mechanism.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 88 lines · 63 tokens per session scan A 703b52a72021
work-audit is a skill published in the GitHub repository xcaeser/work-skill (2 stars, last pushed 2mo ago), licensed MIT. It adds 63 tokens to every session and 1,228 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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