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 acaprino/daodan --skill application-cleanup-methodgit clone --depth 1 https://github.com/acaprino/daodanWrote 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/acaprino/daodan/application-cleanup-method)<a href="https://agentmods.dev/skills/acaprino/daodan/application-cleanup-method"><img src="https://agentmods.dev/badge/skills/acaprino/daodan/application-cleanup-method/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/acaprino/daodan/application-cleanup-method"><img src="https://agentmods.dev/badge/skills/acaprino/daodan/application-cleanup-method.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 | $0.00021 | $0.00224 |
| Opus 5.5 | $0.00008 | $0.00090 |
| Sonnet 5.5 | $0.00004 | $0.00045 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
application-cleanup-method 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 9d 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.
What it actually says
Application cleanup
Input: accepted cleanup findings and severities, target, explicit scope, output root, exclusively owned isolated workspace, clean tree, targeted-fix delivery, commit authorization and required build/test commands. Output: phase ledger with pre-phase SHA, candidate snapshot, gate evidence, commit or verified recovery.
Load the project-protocol:project-protocol skill for execution preflight and the canonical
gate/recovery procedure. Reuse recorded authorization; ask only for missing choices.
Read references/application-cleanup.md inside this skill. Its subtraction method
is promoted from Step 7c without adding a new auditor or a semantic refactor engine.
Inputs can come from a review or an identified lifecycle plan. When targeted fixes
were unnecessary, record 7b as not applicable; otherwise its accepted changes must
be delivered and committed before subtraction. Plain --fix leaves
this commit-only action open and explains the missing capability before execution.
What ships with it
2 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.
- 9d ago First seen · 22 lines · 21 tokens per session scan A 36c992714357
application-cleanup-method is a skill published in the GitHub repository acaprino/daodan (9 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 224 once invoked, about $0.0001 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 2026-10-08.
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