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 ChrisLamDev/hermes-core-skills --skill requesting-code-reviewgit clone --depth 1 https://github.com/ChrisLamDev/hermes-core-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/chrislamdev/hermes-core-skills/requesting-code-review)<a href="https://agentmods.dev/skills/chrislamdev/hermes-core-skills/requesting-code-review"><img src="https://agentmods.dev/badge/skills/chrislamdev/hermes-core-skills/requesting-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.
<a href="https://agentmods.dev/skills/chrislamdev/hermes-core-skills/requesting-code-review"><img src="https://agentmods.dev/badge/skills/chrislamdev/hermes-core-skills/requesting-code-review.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 | $0.00056 | $0.03200 |
| Opus 5.5 | $0.00022 | $0.01280 |
| Sonnet 5.5 | $0.00011 | $0.00640 |
| Haiku 4.5 | $0.00006 | $0.00320 |
Grade A, and why
requesting-code-review scanned grade A with 1 finding 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 1mo 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
os.system(f"ls {user_input}") How it starts
The opening of the file, as written. The whole thing — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Commit Code Verification
Automated verification pipeline before code lands. Static scans, baseline-aware quality gates, an independent reviewer subagent, and an auto-fix loop.
Core principle: No agent should verify its own work. Fresh context finds what you miss.
When to Use
- After implementing a feature or bug fix, before
git commitorgit push - When user says "commit", "push", "ship", "done", "verify", or "review before merge"
- After completing a task with 2+ file edits in a git repo
- After each task in subagent-driven-development (the two-stage review)
Skip for: documentation-only changes, pure config tweaks, or when user says "skip verification".
This skill vs github-code-review: This skill verifies YOUR changes before committing.
github-code-review reviews OTHER people's PRs on GitHub with inline comments.
Step 1 — Get the diff
git diff --cached
If empty, try git diff then git diff HEAD~1 HEAD.
If git diff --cached is empty but git diff shows changes, tell the user to
git add <files> first. If still empty, run git status — nothing to verify.
If the diff exceeds 15,000 characters, split by file:
git diff --name-only
git diff HEAD -- specific_file.py
Step 2 — Static security scan + Threat Model
Scan added lines only. Any match is a security concern fed into Step 5.
快速 Threat Model: 先諗 30 秒像黑客咁思考:
- Map the trust boundaries — Untrusted data 喺邊度入嚟?HTTP request, form fields, file uploads, webhooks, third-party APIs, LLM output
- Name the assets — 邊啲資料值得偷或破壞?Credentials, PII, payment data, admin actions
- Run STRIDE over each boundary — Spoofing? Tampering? Repudiation? Info disclosure? DoS? Elevation?
Scan added lines only. Any match is a security concern fed into Step 5.
# Hardcoded secrets
git diff --cached | grep "^+" | grep -iE "(api_key|secret|password|token|passwd)\s*=\s*['\"][^'\"]{6,}['\"]"
# Shell injection
git diff --cached | grep "^+" | grep -E "os\.system\(|subprocess.*shell=True"
# Dangerous eval/exec
git diff --cached | grep "^+" | grep -E "\beval\(|\bexec\("
# Unsafe deserialization
git diff --cached | grep "^+" | grep -E "pickle\.loads?\("
# SQL injection (string formatting in queries)
git diff --cached | grep "^+" | grep -E "execute\(f\"|\.format\(.*SELECT|\.format\(.*INSERT"
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.
- 1mo ago First seen · 400 lines · 56 tokens per session scan A 49116a8bc8ff
requesting-code-review is a skill published in the GitHub repository ChrisLamDev/hermes-core-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 3,200 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
tuicr
Use tuicr's review CLI to read and add comments in active TUI review sessions, and launch tuicr in cmux, tmux, Zellij, or Herdr when a user needs an interactive review pane.
liveagent-code-review
Review an open GitHub pull request or the current local branch and working tree with parallel, independent reviewers and evidence-based validation. Use when the user asks for code review, invokes the Code Review action from Git Review, or explicitly mentions this skill.
omh-image-cards
This is an OMH img-summary workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
omh-ai-slop-cleaner
This is an OMH ai-slop-cleaner workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
omh-verification-gate
This is an OMH verification-gate workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).