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 orcasecurity/orca-skills --skill orca-inactive-identities-cleanupgit clone --depth 1 https://github.com/orcasecurity/orca-skillsWrote 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/orcasecurity/orca-skills/orca-inactive-identities-cleanup)<a href="https://agentmods.dev/skills/orcasecurity/orca-skills/orca-inactive-identities-cleanup"><img src="https://agentmods.dev/badge/skills/orcasecurity/orca-skills/orca-inactive-identities-cleanup/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/orcasecurity/orca-skills/orca-inactive-identities-cleanup"><img src="https://agentmods.dev/badge/skills/orcasecurity/orca-skills/orca-inactive-identities-cleanup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 253 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00178 | $0.09391 |
| Opus 5 | $0.00089 | $0.04695 |
| Sonnet 5 | $0.00036 | $0.01878 |
| Haiku 4.5 | $0.00018 | $0.00939 |
Grade A, and why
orca-inactive-identities-cleanup 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 12d 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 — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orca Inactive-Identity Cleanup Skill
Answers the question: "Which of our identities are dead weight, and how do we safely disable or delete them?"
Every identity that exists but is never used is pure attack surface: it can be phished, its keys can leak, and nobody notices when it starts doing things. This skill sweeps an account or business unit for inactive users, groups, and non-human identities (NHIs), ranks them by identity risk score, and walks the user through cleanup with a non-destructive path (disable) and a destructive path (delete) that is always gated behind explicit confirmation.
The core signal: every identity Orca covers carries a pre-computed activity verdict on the asset itself: LastActiveTime (when it last did anything) and IsIdentityActive (Orca's uniform 90-day activity convention, computed at scan time). This holds across all six supported providers: AWS, Azure (incl. Entra ID), GCP (incl. Google Workspace), Alibaba Cloud, OCI, and Tencent Cloud. Read the verdict off the asset first; CDR log replay is corroboration, never the primary source.
Usage
/orca-inactive-identities-cleanup 123456789012 # one cloud account
/orca-inactive-identities-cleanup "Production" # a business unit
/orca-inactive-identities-cleanup 123456789012 --inactive 60d # custom time frame (skips the question)
/orca-inactive-identities-cleanup 123456789012 --only nhis # bucket: users | groups | nhis
/orca-inactive-identities-cleanup --tag env=prod # scope by tag (instead of account / BU)
/orca-inactive-identities-cleanup 123456789012 --action disable # pre-select the non-destructive path
Or natural language:
- "clean up inactive identities in acme-production"
- "which users haven't been active in the last 60 days?"
- "find groups nobody uses and get rid of them"
- "disable the dormant service accounts in the Production BU"
- "any stale RAM users in our Alibaba account?"
Processing Logic
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.
- 12d ago First seen · 286 lines · 178 tokens per session scan A e3027b386594
orca-inactive-identities-cleanup is a skill published in the GitHub repository orcasecurity/orca-skills (50 stars, last pushed 5d ago), licensed MIT. It adds 178 tokens to every session and 9,391 once invoked, about $0.0009 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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