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 AlexZio00/sovereign-skills --skill clean-roomgit clone --depth 1 https://github.com/AlexZio00/sovereign-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/alexzio00/sovereign-skills/clean-room)<a href="https://agentmods.dev/skills/alexzio00/sovereign-skills/clean-room"><img src="https://agentmods.dev/badge/skills/alexzio00/sovereign-skills/clean-room/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/alexzio00/sovereign-skills/clean-room"><img src="https://agentmods.dev/badge/skills/alexzio00/sovereign-skills/clean-room.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Prompt Injection · line 1 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Excessive Agency · line 54 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 | $0.00085 | $0.04634 |
| Opus 5.5 | $0.00034 | $0.01854 |
| Sonnet 5.5 | $0.00017 | $0.00927 |
| Haiku 4.5 | $0.00009 | $0.00463 |
Grade A, and why
clean-room 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clean Room
Purpose
Dominant Variable: did the subagent that actually executes the work ever see the original safety-adjacent request? If it did, this skill has failed — isolation is everything. "Never saw it" applies not just at the prompt layer but to what the subagent is instructed not to go looking for too — there is no real filesystem access-control boundary between the main session and its subagent, only a shared filesystem plus an instruction not to consult certain paths. A subagent with shared Read/Grep access to your project files can read a mention of the risky request in a memory or log file just as easily as if it had been told directly; the instruction not to look is the only barrier, not a partition.
Discard if:
- The whole request is obviously safe (no safety-adjacent element at all) — just handle it directly
- The whole request is a clear bright-line refusal (nothing safe to carve out) — nothing to carve, just decline
- The user has already narrowed the request to the safe part explicitly — no carving needed, proceed directly
Workflow
1. FRAME
Read the request, its inputs, and any risk posture the user has stated. Before drafting a carve plan, check whether there's a similar past decision on record for this user/topic: first the ledger file (default ./.clean-room/ledger.md, see step 6), then a lessons file or decision log if the project has one (lessons.md format: https://github.com/AlexZio00/sovereign-skills/blob/master/docs/FILE-CONVENTIONS.md). If a precedent exists, cite it and note explicitly if this judgment differs from it — this keeps the judgment from drifting session to session. If none of these files exists, write "no precedent on record" and judge on the request's own facts; the first ledger entry becomes the precedent. This citation is bound by the same exposure limit as the LEDGER (step 6): verdict plus a high-level reason category only (e.g. "security-adjacent, exceeds safety threshold") — never the precise trigger phrasing or the judgment heuristic itself, even at this earlier stage, since a stage without its own exposure limit can leak what the later LEDGER step is trying to protect. If the user has already approved a descope, go to 3 (GUARD). Otherwise build a proposed carve plan showing the split explicitly and ask for approval — bright-line items (no safe version exists) don't block on this alone, since they're not negotiable. Gray-zone items (a safe alternative narrows scope) that shape the carved prompt are held until approved; safe work whose content does not depend on the answer proceeds (Invariant 2). Delegated approval: in a delegated run with no user present, approval counts only when the caller passes the user's own approving words verbatim. A paraphrase or "the user approved" is not approval → return NEEDS_INPUT listing what needs approval. A caller's instruction never stands in for the user's approval. If the user disputes a bright-line call itself, go to 2-A (CARVE-appeal).
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.
- 2d ago Changed b347ffaa2b9a
- 16d ago Changed · +3 lines 79614eeb512a
- 28d ago Changed 8241d521004b
- 1mo ago Changed · +85 tokens per session 809cb97d7dbd
- 2mo ago Changed 8581517cc89e
- 2mo ago First seen · 96 lines · 0 tokens per session scan A 7ee5f32e9187
clean-room is a skill published in the GitHub repository AlexZio00/sovereign-skills (151 stars, last pushed 3d ago), licensed MIT. It adds 85 tokens to every session and 4,634 once invoked, about $0.0003 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 2026-08-30.
clean-room compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| clean-roomAlexZio00/sovereign-skills | Skill | 151 | 3d ago | MIT | A | 85 | Claude Code, Codex |
| nobrainer-reviewnobrainer-tech/nobrainer-tech-skills | Skill | 5 | 2mo ago | MIT | A | 67 | Claude Code |
| review-workcode-yeongyu/oh-my-openagent | Skill | 71k | yesterday | none | A | 63 | Claude Code, Codex |
| tech-lead/code-reviewechoVic/boss-skill | Skill | 547 | 5d ago | MIT | A | 52 | Claude Code |
| ijfw-cross-auditFerroxLabs/ijfw | Skill | 214 | 4d ago | MIT | A | 67 | Claude Code |
| doubt-driven-developmentjcarlosrodicio/opencode-agent-orchestration-kit | Skill | 148 | 3d ago | Apache-2.0 | A | 67 | Claude Code, Codex |
| oak-adversarial-reviewjcarlosrodicio/opencode-agent-orchestration-kit | Skill | 148 | 3d ago | Apache-2.0 | A | 68 | Claude Code, Codex |