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/steipete/agent-scripts/skill-cleanernpx skills add steipete/agent-scripts --skill skill-cleanergit clone --depth 1 https://github.com/steipete/agent-scriptsWhat 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 | $0.00022 | $0.00958 |
| Opus 5 | $0.00011 | $0.00479 |
| Sonnet 5 | $0.00004 | $0.00192 |
| Haiku 4.5 | $0.00002 | $0.00096 |
Grade A, and why
skill-cleaner 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Cleaner
Use this when trimming skill prompt budget, finding duplicate skills, auditing enabled/disabled skill roots, or deciding which skills/plugins to remove.
Workflow
- Run the analyzer from this skill directory or repo root:
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --months 3
Useful variants:
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --no-logs
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --no-live --no-logs
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --months 6 --max-log-mb 800 --deep-logs
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --context-tokens 272000 --budget-percent 2 --no-logs
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --root ~/Dropbox/boxd/skills --no-logs
node --experimental-strip-types skills/skill-cleaner/scripts/skill-cleaner.ts --root ~/.agents/skills --root-only --no-logs
- Read the report in this order:
Skill Budget: live Codex inventory, 2% budget, budgeted usage, and full-description pressure.Description candidates: long descriptions where relaxed grammar saves prompt budget.Duplicates: same skill name or near-identical description/body across Codex, plugin cache, repo siblings, and personal skill roots.Unused candidates: no recent user mention or actualSKILL.mdread in recent Codex/OpenClaw logs.Root summary: where skills came from and whether config marks them disabled.
- Before deleting or editing:
- Verify the kept copy exists and is loaded.
- Prefer deleting repo-local or
agent-scriptsduplicates when Codex built-ins cover them. - Keep repo-local OpenClaw maintainer skills when they encode repo policy or live operations.
- Preserve trigger nouns in descriptions: product, tool, action, object.
Analyzer Notes
- By default,
codex debug prompt-inputsupplies the exact model-visible skill list, order, names, and aliased paths.--no-liveforces the broader filesystem fallback. - The broad filesystem scan remains for duplicate, disabled, and archived-cache diagnostics; it is not treated as the loaded inventory.
- The script mirrors Codex's model-visible line shape:
- name: description (file: path). - It applies Codex-like frontmatter rules: YAML frontmatter only, default name from parent dir, single-line sanitized
nameanddescription. - It follows Codex
core-skills/src/render.rs: 2% of rawcontext_window, token costceil(utf8_bytes / 4), then full descriptions -> equal description truncation -> omitted minimum lines. Alias-table line cost is included. - It reads
~/.codex/models_cache.jsonfor GPT-5.5context_window; fallback is 272,000 tokens and 2%. - It scans only normal Codex/plugin/repo skill roots by default. Extra folders such as Dropbox archives are included only with
--root <path>. --root-onlyrequires at least one--root <path>, skips the live Codex inventory, and scans only those supplied roots.- It realpath-dedupes roots, so symlinked roots such as
~/.codex/skills/agent-scripts -> ~/Projects/agent-scripts/skillsdo not create false duplicates. - For duplicate names, it reports description/body similarity and suggests deletion candidates only when bodies are near copies. Keep priority defaults to direct Codex system skills, then direct Codex skills, then plugin skills, then personal/repo copies.
- It scans
~/.codex/history.jsonland recent~/.codex/sessions/**/*.jsonlby default. Add--deep-logsfor archived sessions and common OpenClaw/Clawd log folders. - Usage evidence is heuristic: user
$skill/use skillmentions and paths observed in tool-call arguments.
What ships with it
3 files 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 · 62 lines · 22 tokens per session scan A 32e482ba1794
skill-cleaner is a skill published in the GitHub repository steipete/agent-scripts (6,590 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 958 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 2026-08-30.
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