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 skills/xcaeser/work-skill/work-cleannpx skills add xcaeser/work-skill --skill work-cleangit clone --depth 1 https://github.com/xcaeser/work-skillWhat 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 | $0.00065 | $0.01303 |
| Opus 5 | $0.00032 | $0.00651 |
| Sonnet 5 | $0.00013 | $0.00261 |
| Haiku 4.5 | $0.00006 | $0.00130 |
Grade A, and why
work-clean 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 2d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Work / 8. Clean
Find defensible simplifications without editing. The Sol xhigh analyst remains read-only; the parent owns every cleanup decision and any later execution route.
Preserve reliability, restraint, user data, meaningful tests, and the simplest complete implementation. Remove obsolete paths instead of preserving compatibility, and require evidence for every deletion or abstraction change.
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 cleanup analysis in the parent. - Launch exactly one
gpt-5.6-solsubagent atxhigheffort withfork_turns: none. - Give it a fun call sign, the exact task statement, exact scope, source of truth, behavior boundaries, package constraints, acceptance checks, and validation requirements.
- Require independent analysis and concrete evidence for every proposed deletion or shared component; do not accept a status report, speculative smell, or “routine” migration.
- Require it to call
create_goalwith the exact cleanup-analysis goal before inspection andupdate_goal completeonly after the required checks pass. - Let the analyst run until it returns the cleanup plan, 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 scope. Inspect only relevant paths, direct consumers, and evidence needed to prove each simplification; return the plan without process narration and stop when every candidate has a supported disposition.
- Report the successful launch as a compact table with
Agent,Working on,Goal,Ownership, andModel.
Analysis
- Prefer an explicit path, subsystem, feature, or diff; otherwise use the smallest scope clearly implied by the request.
- Inspect instructions, status, relevant diffs, consumers, registrations, generated outputs, existing tests, public APIs, and actual user flows.
- Identify dead code, needless indirection, duplicate behavior, speculative abstractions, and unclear boundaries.
- Keep helpers that communicate intent, isolate side effects, improve testing, or have genuine reuse. Simplify the consumer path; do not merely move complexity into a new wrapper or hide it behind a renamed abstraction.
- Consider packages in this order: standard library/platform, an existing project dependency, a mature and battle-tested external package, then focused local code. Check existing dependency documentation and types before reimplementing functionality or adding a package. Choose a package only when its reliability, maintenance, license, runtime fit, and reduced complexity earn the dependency cost; record chosen and rejected options with reasons.
- Challenge cleanup candidates against exact behavior, error paths, partial state, retries, interruption, permissions, upgrades, and recovery before recommending removal.
- Preserve meaningful tests and remove only tests that are demonstrably obsolete, tautological, framework-level, or detached from a real contract. Do not add coverage-only tests.
- Prefer durable architecture over a stopgap intended to be replaced later. Do not propose behavior, API, persistence, security, UX, test, or type weakening without explicit authorization.
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.
- 2d ago First seen · 87 lines · 65 tokens per session scan A b70eaf67dbe6
work-clean is a skill published in the GitHub repository xcaeser/work-skill (2 stars, last pushed 22d ago), licensed MIT. It adds 65 tokens to every session and 1,303 once invoked, about $0.0003 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.
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