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 agentmods add skills/naimkatiman/continuous-improvement/code-review-and-qualitynpx skills add naimkatiman/continuous-improvement --skill code-review-and-qualitygit clone --depth 1 https://github.com/naimkatiman/continuous-improvementWrote 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/naimkatiman/continuous-improvement/code-review-and-quality)<a href="https://agentmods.dev/skills/naimkatiman/continuous-improvement/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/naimkatiman/continuous-improvement/code-review-and-quality.svg" alt="Measured on agentmods" 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 | $0.00051 | $0.03040 |
| Opus 5 | $0.00026 | $0.01520 |
| Sonnet 5 | $0.00010 | $0.00608 |
| Haiku 4.5 | $0.00005 | $0.00304 |
Grade A, and why
code-review-and-quality 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 2d 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
83% identical to code-review-and-quality — 57 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 — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review and Quality
Overview
Multi-dimensional code review with quality gates. Every change gets reviewed before merge — no exceptions. Review covers five axes: correctness, readability, architecture, security, and performance.
The approval standard: Approve a change when it definitely improves overall code health, even if it isn't perfect. Perfect code doesn't exist — the goal is continuous improvement. Don't block a change because it isn't exactly how you would have written it. If it improves the codebase and follows the project's conventions, approve it.
When to Use
- Before merging any PR or change
- After completing a feature implementation
- When another agent or model produced code you need to evaluate
- When refactoring existing code
- After any bug fix (review both the fix and the regression test)
The Five-Axis Review
Every review evaluates code across these dimensions:
1. Correctness
Does the code do what it claims to do?
- Does it match the spec or task requirements?
- Are edge cases handled (null, empty, boundary values)?
- Are error paths handled (not just the happy path)?
- Does it pass all tests? Are the tests actually testing the right things?
- Are there off-by-one errors, race conditions, or state inconsistencies?
2. Readability & Simplicity
Can another engineer (or agent) understand this code without the author explaining it?
- Are names descriptive and consistent with project conventions? (No
temp,data,resultwithout context) - Is the control flow straightforward (avoid nested ternaries, deep callbacks)?
- Is the code organized logically (related code grouped, clear module boundaries)?
- Are there any "clever" tricks that should be simplified?
- Could this be done in fewer lines? (1000 lines where 100 suffice is a failure)
- Are abstractions earning their complexity? (Don't generalize until the third use case)
- Would comments help clarify non-obvious intent? (But don't comment obvious code.)
- Are there dead code artifacts: no-op variables (
_unused), backwards-compat shims, or// removedcomments?
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.
- 2d ago First seen · 348 lines · 51 tokens per session scan A 7587de5eff9e
code-review-and-quality is a skill published in the GitHub repository naimkatiman/continuous-improvement (7 stars, last pushed 11d ago), licensed MIT. It adds 51 tokens to every session and 3,040 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to code-review-and-quality, differing in 57 lines, and is treated as a copy.
Other skills, from other repositories
code-standards
Prabhdeep (Sonu) Singh's personal coding standards — the house rules and quality bar for how code gets written. INVOKE before writing, generating, refactoring, or reviewing ANY code in ANY language — schemas, endpoints, queries, logging, validation, error handling — even when nobody says "standards" or "style".…
self-review
Surface the riskiest parts of the current diff so a reviewer knows where to look hardest — one inline pass on small diffs, parallel review lenses with adversarial synthesis on substantial ones. INVOKE PROACTIVELY whenever a change is finished and about to be handed off, reviewed, or shipped. It points attention …
bug-finder
Hunt for one real, previously unreported defect and file it as a well-evidenced ticket — proactive discovery, not reactive diagnosis. INVOKE when asked to sweep code for bugs or hunt risky areas, and when /sonu:factory runs a bug-hunt pass. A known symptom is [[debugging]]; a pending diff is [[self-review]]. It files…
continual-learning
Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…
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.
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.…