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 hnikoloski/imlazy --skill imlazy-code-reviewgit clone --depth 1 https://github.com/hnikoloski/imlazyWrote 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/hnikoloski/imlazy/imlazy-code-review)<a href="https://agentmods.dev/skills/hnikoloski/imlazy/imlazy-code-review"><img src="https://agentmods.dev/badge/skills/hnikoloski/imlazy/imlazy-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/hnikoloski/imlazy/imlazy-code-review"><img src="https://agentmods.dev/badge/skills/hnikoloski/imlazy/imlazy-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 | $0.00042 | $0.00534 |
| Opus 5 | $0.00021 | $0.00267 |
| Sonnet 5 | $0.00008 | $0.00107 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
code-review
When to use
- After each task in
planning(full mode) - Before merging a feature
- When stuck (fresh perspective unblocks you)
- After fixing a complex bug
Requesting a review
Step 1: Get git SHAs
BASE_SHA=$(git rev-parse HEAD~1) # or origin/main for pre-merge review
HEAD_SHA=$(git rev-parse HEAD)
Step 2: Dispatch code reviewer subagent using the template at code-reviewer.md (next to this skill). Fill in:
{DESCRIPTION}— brief summary of what was built{PLAN_OR_REQUIREMENTS}— what it should do{BASE_SHA}/{HEAD_SHA}— the commit range{GIT_DIFF}— output ofgit diff BASE_SHA..HEAD_SHA
Step 3: Act on feedback
- Critical → fix immediately, re-review
- Important → fix before proceeding
- Minor → note for later
- Reviewer is wrong → push back with technical reasoning and evidence; don't blind-implement
Never skip review because "it's simple". Never ignore Critical issues. Never proceed with unfixed Important issues.
Receiving a review
When you receive code review feedback, apply this process before implementing anything:
-
Verify the feedback is technically correct. Read the cited file and line. Does the issue actually exist there?
-
Distinguish severity. Critical issues block progress. Important issues should be fixed. Minor issues are optional. If the reviewer didn't label severity, ask for clarification.
-
Never blind-implement Critical feedback without checking it first. A reviewer can be wrong. If something feels off, verify with a test or look at the actual code.
-
Push back when the reviewer is wrong. "The test at line 42 already covers that edge case — here is the assertion: [paste test]." Technical evidence beats assertion.
-
Fix, then re-request review. Don't mark "fixed" without actually running the test suite.
Common pitfalls:
- Implementing all feedback without verifying — can introduce new bugs
- Dismissing feedback without checking — misses real issues
- Treating Minor as Critical — wastes time on low-impact polish
What ships with it
1 file 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.
- 10d ago First seen · 55 lines · 42 tokens per session scan A 090a744a36d5
code-review is a skill published in the GitHub repository hnikoloski/imlazy (2 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 534 once invoked, about $0.0002 per session on Opus 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
code-review-excellence
This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code review.
tfx-analysis
A code and architecture analysis workflow that can ask several command-line agents to examine a project from different viewpoints, including architecture, security, performance, user experience, and documentation.
tfx-prune
A cleanup workflow that asks three AI coding assistants to independently identify unnecessary code, then removes only issues they agree are unwanted. It checks for duplication, needless abstractions, excessive error handling, and similar readability problems.
tfx-review
A code-review workflow that asks several command-line AI reviewers to inspect changes independently, then reports issues that at least two reviewers agree on. TDD means test-driven development, where tests are written to guide implementation, but this add-on is for reviewing code rather than defining TDD.
do-it-review
Use to assess requirements and implementation quality independently, or to resolve a batch of review findings.
done
Run the closeout ritual before handing back non-trivial work; full verification, revert-probe honesty, independent review, and scope reporting. Use before declaring completion, opening a PR, wrapping up a change, or "ปิดงาน".