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 joao-aires/agent-skills-public --skill operational-housekeepinggit clone --depth 1 https://github.com/joao-aires/agent-skills-publicWrote 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/joao-aires/agent-skills-public/operational-housekeeping)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/operational-housekeeping"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/operational-housekeeping/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/joao-aires/agent-skills-public/operational-housekeeping"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/operational-housekeeping.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 | $0.00035 | $0.01076 |
| Opus 5.5 | $0.00014 | $0.00430 |
| Sonnet 5.5 | $0.00007 | $0.00215 |
| Haiku 4.5 | $0.00003 | $0.00108 |
Grade A, and why
operational-housekeeping 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 yesterday.
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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Operational housekeeping
Read composition guidance for optional expertise, fallback and scope.
Review the operating conditions that drift between feature changes: capacity, retention, expiry, ownership and procedures. For each check, establish which decision its result can trigger and the evidence needed to make that decision. A check with no useful response creates recurring reporting work without improving the system.
Compare the current observation with the previous finding and local policy. Preserve unresolved age, exceptions and ownership so a repeated run follows work through rather than rediscovering it as new. Keep the review finite and return accountable findings; deeper remediation can be a separate scoped action.
Modes and general purpose
- In interactive work, explain review findings and resolve local policy/ownership decisions.
- For setup build a risk-based review register and automate stable checks.
- During features/maintenance update capacity, retention, ownership and procedure requirements affected by the change.
- In recurring review runs consume the last reviewed revision/register, collect current evidence, update stable findings and prepare bounded remedies.
Cleanup/resource mutations need a configured target/action policy; otherwise return candidates and patches rather than deleting anything.
The general value is preventing operational debt and reducing toil, not reproducing a project's calendar. Prefer event-driven checks after configuration/releases/ownership changes, backed by periodic review for drift. Retire checks with no decision value and measure whether automation reduced manual effort without weakening outcomes.
Establish the review
Discover services/environments, owners, resource inventories, local schedules, quota/retention policy, active incidents, and prior exceptions. Start from the project's actual checklist rather than imposing a fixed weekly/monthly calendar.
For a new checklist, assign cadence based on failure consequence, rate of change, expiry lead time, and available automation. Explicitly label proposed cadence or thresholds until adopted.
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.
- yesterday Changed · +7 lines c4cbe37ec0d5
- 2d ago Changed · +2 lines de6e3888e149
- 7d ago First seen · 65 lines · 35 tokens per session scan A bc82a6f7d604
operational-housekeeping is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 1,076 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 2026-10-15.
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