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/manhvann/codexkit/code-reviewnpx skills add manhvann/codexkit --skill code-reviewgit clone --depth 1 https://github.com/manhvann/codexkitWhat 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 | $0.00046 | $0.01302 |
| Opus 5 | $0.00023 | $0.00651 |
| Sonnet 5 | $0.00009 | $0.00260 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
ck: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 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.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Guide proper code review practices emphasizing technical rigor, evidence-based claims, and verification over performative responses.
Default (No Arguments)
If invoked with context (recent changes/PR), proceed with review. If invoked WITHOUT arguments, ask the user to choose available review operations:
| Operation | Description |
|---|---|
(default) |
Review recent changes/PR |
codebase |
Full codebase scan & analysis |
codebase parallel |
Parallel multi-reviewer audit |
Present options with header "Review Operation", question "What would you like to do?".
Core Principle
YAGNI, KISS, DRY always. Technical correctness over social comfort. Be honest, be brutal, straight to the point, and be concise.
Verify before implementing. Ask before assuming. Evidence before claims.
Practices
| Practice | When | Reference |
|---|---|---|
| Receiving feedback | Unclear feedback, external reviewers, needs prioritization | references/code-review-reception.md |
| Requesting review | After tasks, before merge, stuck on problem | references/requesting-code-review.md |
| Verification gates | Before any completion claim, commit, PR | references/verification-before-completion.md |
| Edge case scouting | After implementation, before review | references/edge-case-scouting.md |
| Task-managed reviews | Multi-file features (3+ files), parallel reviewers, fix cycles | references/task-management-reviews.md |
Quick Decision Tree
SITUATION?
│
├─ Received feedback → STOP if unclear, verify if external, implement if human partner
├─ Completed work → Scout edge cases → Request code_reviewer subagent
├─ Multi-file feature (3+ files) → Create review pipeline tasks (scout→review→fix→verify)
└─ About to claim status → RUN verification command FIRST
Receiving Feedback
Pattern: READ → UNDERSTAND → VERIFY → EVALUATE → RESPOND → IMPLEMENT
Rules:
- No performative agreement: "You're absolutely right!", "Great point!"
- No implementation before verification
- Restate, ask questions, push back with reasoning, or just work
- YAGNI check: grep for usage before implementing "proper" features
What ships with it
7 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.
- references/code-review-reception.md 3.0 KB
- references/codebase-scan-workflow.md 1.1 KB
- references/edge-case-scouting.md 2.9 KB
- references/parallel-review-workflow.md 1.9 KB
- references/requesting-code-review.md 3.0 KB
- references/task-management-reviews.md 4.8 KB
- references/verification-before-completion.md 4.1 KB
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 · 148 lines · 46 tokens per session scan A a4f32efd519d
ck:code-review is a skill published in the GitHub repository manhvann/codexkit (88 stars, last pushed 3d ago), licensed MIT. It adds 46 tokens to every session and 1,302 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 2026-08-30.
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