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 LuizEduPP/Rememb --skill code-reviewergit clone --depth 1 https://github.com/LuizEduPP/RemembWrote 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/luizedupp/rememb/code-reviewer)<a href="https://agentmods.dev/skills/luizedupp/rememb/code-reviewer"><img src="https://agentmods.dev/badge/skills/luizedupp/rememb/code-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/skills/luizedupp/rememb/code-reviewer"><img src="https://agentmods.dev/badge/skills/luizedupp/rememb/code-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 | $0.00065 | $0.01187 |
| Opus 5.5 | $0.00026 | $0.00475 |
| Sonnet 5.5 | $0.00013 | $0.00237 |
| Haiku 4.5 | $0.00006 | $0.00119 |
Grade A, and why
code-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 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.
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.
This is a copy
89% identical to code-reviewer — 24 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Reviewer
Automated code review tools for analyzing pull requests, detecting code quality issues, and generating review reports.
Table of Contents
Tools
PR Analyzer
Analyzes git diff between branches to assess review complexity and identify risks.
# Analyze current branch against main
python scripts/pr_analyzer.py /path/to/repo
# Compare specific branches
python scripts/pr_analyzer.py . --base main --head feature-branch
# JSON output for integration
python scripts/pr_analyzer.py /path/to/repo --json
What it detects:
- Hardcoded secrets (passwords, API keys, tokens)
- SQL injection patterns (string concatenation in queries)
- Debug statements (debugger, console.log)
- ESLint rule disabling
- TypeScript
anytypes - TODO/FIXME comments
Output includes:
- Complexity score (1-10)
- Risk categorization (critical, high, medium, low)
- File prioritization for review order
- Commit message validation
Code Quality Checker
Analyzes source code for structural issues, code smells, and SOLID violations.
# Analyze a directory
python scripts/code_quality_checker.py /path/to/code
# Analyze specific language
python scripts/code_quality_checker.py . --language python
# JSON output
python scripts/code_quality_checker.py /path/to/code --json
What it detects:
- Long functions (>50 lines)
- Large files (>500 lines)
- God classes (>20 methods)
- Deep nesting (>4 levels)
- Too many parameters (>5)
- High cyclomatic complexity
- Missing error handling
- Unused imports
- Magic numbers
Thresholds:
| Issue | Threshold |
|---|---|
| Long function | >50 lines |
| Large file | >500 lines |
| God class | >20 methods |
| Too many params | >5 |
| Deep nesting | >4 levels |
| High complexity | >10 branches |
What ships with it
6 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.
- 1mo ago First seen · 198 lines · 65 tokens per session scan A ba4a2d057513
code-reviewer is a skill published in the GitHub repository LuizEduPP/Rememb (5 stars, last pushed 11d ago), licensed MIT. It adds 65 tokens to every session and 1,187 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to code-reviewer, differing in 24 lines, and is treated as a copy.
Other skills, from other repositories
code-review
Review a diff against its acceptance criteria in four segments (convention adherence, bug scan, historical-context regressions, test-coverage gaps) as a NON-implementing agent. Findings are sorted by severity, each with file:line + a failure scenario. A planted defect must be caught; a clean diff must not be…
design-review
Five-dimension design audit (frontend UI/UX · server data-model & flow · endpoint spec · daemon-runtime/SDK & local-cache-first · built-in skill/agent-role), executed by a NON-implementing agent. Every dimension gets a verdict; N/A only with a stated reason. A dimension the design silently skipped must be surfaced as…
codebase-design
Design maintainable module interfaces, review scoped code changes, and simplify implementations with behavioral verification. Use for code review, cleanup, testability, and module design work.
code-review
Use when asked to review a PR, MR, branch, or diff, audit changed files, or check code quality.
prismer-github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
pre-pr
Prepare a Honcho change for a pull request to plastic-labs/honcho. Invoke before opening a PR, when drafting a PR body, when asked if a branch is PR-ready, or when filling the pull request template. Checks the linked issue, required tests and docs, then writes Description / Proofs / Fixes.