agent-claim-network: Skill for Claude Code

.agents/skills/code-review/SKILL.md

code-review is a skill for Claude Code, Codex from FTShare-Lab/agent-claim-network. It costs 41 tokens per session (1,091 once invoked), scanned A, original, Apache-2.0.

A multi-pass code-review workflow that examines local changes and asks an independent read-only reviewer to check them as well. It focuses on real defects in logic, state changes, persistence, concurrency, security, user-visible behavior, and tests.

In plain words
What is it for?
Use it before merging code or after a significant refactor, especially when changes affect asynchronous work, stored data, terminal interfaces, tools, secrets, or network boundaries.
Why use it?
It provides a second review of important changes and helps identify failures that a single inspection may overlook. It keeps unrelated work in the repository untouched.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; runs codex exec; installed under .agents/ (shared by several agents).

This is FTShare-Lab/agent-claim-network's own configuration. It tells Claude Code and Codex how to work on agent-claim-network itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agent-claim-network configures →

Reuse

Borrowing it

Nothing to install: this file belongs to FTShare-Lab/agent-claim-network. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/FTShare-Lab/agent-claim-network/main/.agents/skills/code-review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/FTShare-Lab/agent-claim-network

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for code-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/ftshare-lab/agent-claim-network/code-review/github.svg)](https://agentmods.dev/skills/ftshare-lab/agent-claim-network/code-review)
Your own site
<a href="https://agentmods.dev/skills/ftshare-lab/agent-claim-network/code-review"><img src="https://agentmods.dev/badge/skills/ftshare-lab/agent-claim-network/code-review/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.

agentmods 80×15 button for code-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/ftshare-lab/agent-claim-network/code-review"><img src="https://agentmods.dev/badge/skills/ftshare-lab/agent-claim-network/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,091 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.01091
Opus 5.5 $0.00016 $0.00436
Sonnet 5.5 $0.00008 $0.00218
Haiku 4.5 $0.00004 $0.00109

Measured 2mo ago against content hash b24c890c3e76, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-review 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.

.agents/skills/code-review/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-Pass Code Review

1. Define the review range

Inspect git status, the relevant diff, and the surrounding implementation. Preserve unrelated working-tree changes. Review the code that actually runs; do not substitute an old PRD for the current behavior.

2. Perform the local review

Follow the repository's AGENTS.md and focus on actionable defects:

  • business-logic and state-transition gaps;
  • persistence, recovery, compatibility, and protocol-boundary problems;
  • async blocking, cancellation, locking, process-lifecycle, and resource leaks;
  • tool authorization, path handling, secrets, and network exposure;
  • user-visible TUI errors, misleading status, and broken interaction flows;
  • missing tests for realistic failure paths.

Do not report formatting already covered by rustfmt, speculative low-probability crashes without a credible trigger, or style preferences that do not affect correctness or maintainability.

Unless the user explicitly requests a broader review, use this default severity boundary:

  • Ignore extreme edge cases and crashes, layout shifts, or state mismatches assessed as extremely unlikely. Do not inflate them into actionable findings.
  • Keep the actionable and automatic-fix set to P0 and P1 findings with a realistic trigger and material impact.
  • Prioritize real business-logic, security/data-integrity, and user-visible TUI defects. Do not automatically fix P2/P3 findings; mention a lower-severity item only when it materially affects a decision, and leave it deferred unless the user expands the scope.

3. Obtain an external Codex review

Run one direct, read-only codex exec --json review pass. The external prompt must forbid invoking this skill, running another codex process, calling delegation tools, or modifying files.

Requirements:

  1. Require codex to be available on PATH; do not source a personal shell startup file.
  2. Create a run directory with mktemp -d outside the repository.
  3. Save JSONL, stderr, and the final response so partial output survives interruption.
  4. Use the Codex CLI's configured default model. Only pass -m when REVIEW_MODEL is explicitly set by the caller.
  5. Default the external timeout to 30 minutes (1800 seconds), overridable through REVIEW_TIMEOUT_SECONDS.
  6. If the review times out, inspect partial artifacts, split the diff into smaller review units, and retry. Do not declare the external pass complete without a usable result.

Read the full file on GitHub · 91 lines

Changes

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.

  1. 2mo ago First seen · 91 lines · 41 tokens per session scan A b24c890c3e76

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository FTShare-Lab/agent-claim-network (44 stars, last pushed 3d ago), licensed Apache-2.0. It adds 41 tokens to every session and 1,091 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

github-code-review

Review code changes by analyzing git diffs, leaving inline comments on PRs, and performing thorough pre-push review. Works with gh CLI or falls back to git + GitHub REST API via curl.

moltis-org/moltis · 45 tokens

kverus-review

Review uncommitted or recent Verus code changes for exec-code modifications, unnecessary == introductions, and verification issues. Use before committing to catch regressions in executable semantics, set reasoning, and proof quality.

asterinas/KVerus · 47 tokens

kverus-postprocess

Final cleanup for Verus proof changes: consume cached dynamic review rules, delegate stale GitHub refreshes to a subagent, verify, simplify redundant proof code through kverus-strip, format, and run local checks. Use after proof-sensitive KVerus work or before finalizing Verus changes.

asterinas/KVerus · 66 tokens

review

Review code changes, pull requests, patches, or a scoped code area for actionable correctness, security, compatibility, and test risks with file and line evidence. Use for review or audit requests; do not use for general proofreading, feature implementation, or debugging a reported failure when the user wants a fix.

bigduu/Bamboo-agent · 62 tokens

code-review-feedback

Use when receiving code-review feedback, before implementing suggestions — especially when feedback seems unclear or technically questionable. Verify against the codebase and reason about each item instead of agreeing performatively or implementing blindly.

dirge-code/dirge · 43 tokens

debug

Diagnose a concrete failure, regression, crash, hang, flaky test, or incorrect runtime behavior by reproducing it, testing hypotheses, and identifying the evidence-backed root cause. Use when symptoms or failing output exist; do not use for feature implementation without a failure, general code review, or a conceptual…

bigduu/Bamboo-agent · 64 tokens