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 techgangboss/agentstore --skill code-reviewergit clone --depth 1 https://github.com/techgangboss/agentstoreWrote 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/techgangboss/agentstore/code-reviewer)<a href="https://agentmods.dev/skills/techgangboss/agentstore/code-reviewer"><img src="https://agentmods.dev/badge/skills/techgangboss/agentstore/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/techgangboss/agentstore/code-reviewer"><img src="https://agentmods.dev/badge/skills/techgangboss/agentstore/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 | $0.00070 | $0.00563 |
| Opus 5.5 | $0.00028 | $0.00225 |
| Sonnet 5.5 | $0.00014 | $0.00113 |
| Haiku 4.5 | $0.00007 | $0.00056 |
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.
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.
Code Reviewer
AI-powered code review that analyzes code for bugs, security vulnerabilities, performance issues, and adherence to best practices.
Capabilities
- Bug detection and logical error analysis
- Security vulnerability scanning (OWASP Top 10)
- Performance issue identification
- Best practice and style suggestions
- Dependency risk assessment
Instructions
When the user asks for a code review:
1. Gather Context
- Identify the files to review (user may specify, or review staged/changed files via
git diff) - Determine the language and framework
- Check for project conventions (linting config,
.editorconfig, etc.)
2. Analyze for Issues
Review each file systematically for:
Bugs & Logic Errors:
- Off-by-one errors, null/undefined access, race conditions
- Incorrect type handling, missing error cases
- Logic that doesn't match stated intent
Security (OWASP Top 10):
- SQL injection, XSS, command injection
- Hardcoded secrets or credentials
- Insecure deserialization, SSRF
- Missing input validation at system boundaries
- Improper authentication/authorization checks
Performance:
- N+1 queries, unnecessary re-renders
- Missing indexes for database queries
- Unbounded loops or memory leaks
- Synchronous operations that should be async
Best Practices:
- Dead code, unused variables/imports
- Missing error handling at API boundaries
- Inconsistent naming conventions
- Functions doing too many things
3. Report Findings
Format the review as:
## Code Review Summary
### Critical Issues (must fix)
- [FILE:LINE] Description of critical bug or security issue
### Warnings (should fix)
- [FILE:LINE] Description of potential problem
### Suggestions (nice to have)
- [FILE:LINE] Style or best practice improvement
### What Looks Good
- Positive observations about well-written code
4. Offer Fixes
For each critical issue and warning, offer to generate a fix. Use the Edit tool to apply fixes the user approves.
Example
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 · 91 lines · 70 tokens per session scan A c74f4b1a675a
code-reviewer is a skill published in the GitHub repository techgangboss/agentstore (4 stars, last pushed 8mo ago), licensed MIT. It adds 70 tokens to every session and 563 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 2026-08-31.
Other skills, from other repositories
merge-batch
Prepare and merge an owner-selected PR batch with contributor credit and exact-candidate admission. Use for a pasted PR list; combined focused validation is diagnostic, and every actual landing still requires its applicable checks and authorization.
make-pr-easy-to-review
Prepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".
review-work
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed work.
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…
security-review
Perform a focused security review of pending git changes to identify high-confidence security vulnerabilities with real exploitation potential. Use this skill when the user asks for a security review, security audit, vulnerability scan, or wants to check pending changes on a branch for security issues before merging.…
huggingface-llm-trainer
Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion. Use for cloud LLM training; use huggingface-vision-trainer for vision tasks.