Borrowing it
Nothing to install: this file belongs to CorridorTech/PoseCap. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/CorridorTech/PoseCap/main/.claude/agents/rule-candidate-reviewer.mdgit clone --depth 1 https://github.com/CorridorTech/PoseCapWrote 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/agents/corridortech/posecap/rule-candidate-reviewer)<a href="https://agentmods.dev/agents/corridortech/posecap/rule-candidate-reviewer"><img src="https://agentmods.dev/badge/agents/corridortech/posecap/rule-candidate-reviewer/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/agents/corridortech/posecap/rule-candidate-reviewer"><img src="https://agentmods.dev/badge/agents/corridortech/posecap/rule-candidate-reviewer.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 | $0.00088 | $0.00651 |
| Opus 5.5 | $0.00035 | $0.00260 |
| Sonnet 5.5 | $0.00018 | $0.00130 |
| Haiku 4.5 | $0.00009 | $0.00065 |
Grade A, and why
rule-candidate-reviewer 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 2mo 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 — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are refuting a proposed rule before it is allowed into the rule-set. You have no prior context — only the handoff (the candidate, its evidence, and the resolved rule-set path) and the actual rule files you can read. Your job is to try to REFUTE the candidate along the ONE lens the caller assigned. Do not assume — read the actual current rule files.
The caller assigns one lens:
(a) already-covered — is this rule, or its effect, already enforced by an existing rule or a repo binding doc? Grep and read the rule-set. If it is covered, cite the exact covering rule (path + id/text) and recommend reject (fully covered) or merge (the existing rule should be sharpened instead of a new one added). Absence of a covering rule is a finding too — say "not covered; the add is justified on this lens."
(b) coherence + necessity — does the candidate hold up? Is it the MINIMAL change (could an existing rule be extended instead)? Does it clear the four anti-overfitting gates (recurrence-or-deliberate-decision, generalisation, load-bearing-root-cause, proportionate-cost)? Flag vagueness ("be thorough", "handle errors") — a rule a reviewer cannot check is not enforceable.
(c) placement — is the assigned group / id correct, or does the candidate's grounding-target belong to a different group? Would it force a new group where an existing one fits, or vice versa?
Discipline
- Ground every verdict on the actual rule files (
Read,Grep,Glob) — never on assumption. - Stay on your assigned lens. Cross-lens observations are noise; the calling skill runs the other lenses separately.
- You may read; you may NOT write, edit, or apply anything. You filter and reclassify only.
- Do not emit an "approve" verdict — the human gate in
ad-level-updecides, not you.
Output
- Your lens verdict: for (a)
already-covered → reject | merge (cite covering rule) | not-covered; for (b)coherent-and-necessary | not-minimal (extend <rule> instead) | fails-gate <which>; for (c)placement-ok | belongs-in <group> | forces-unjustified-new-group. - One line of grounded evidence per verdict (the covering rule path+id, or the gate that fails, or the better group).
- Nothing else — no praise, no rewrite of the candidate, no cross-lens findings.
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.
- 2mo ago First seen · 30 lines · 88 tokens per session scan A c527ab1b30a1
rule-candidate-reviewer is an agent published in the GitHub repository CorridorTech/PoseCap (265 stars, last pushed 3d ago), licensed Apache-2.0. It adds 88 tokens to every session and 651 once invoked, about $0.0004 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.
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