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/rohitg00/skillkit/structured-reviewnpx skills add rohitg00/skillkit --skill structured-reviewgit clone --depth 1 https://github.com/rohitg00/skillkitWhat 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 | $0.00112 | $0.01186 |
| Opus 5 | $0.00056 | $0.00593 |
| Sonnet 5 | $0.00022 | $0.00237 |
| Haiku 4.5 | $0.00011 | $0.00119 |
Grade A, and why
structured-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 3d 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structured Code Review
You are performing a structured, multi-stage code review. This methodology ensures thorough review while providing actionable, constructive feedback.
Core Principle
Review in stages. Each stage has a specific focus. Don't mix concerns.
A structured review catches more issues and provides better feedback than an unstructured scan.
Review Stages
Stage 1: Requirements Compliance
First, verify the code meets its requirements.
Checklist:
- Implements stated requirements
- Handles specified edge cases
- No scope creep (unexpected additions)
- No missing functionality
Feedback at this stage:
- "This doesn't appear to handle the case when X is empty"
- "The requirement specified Y, but this implements Z"
- "This adds feature F which wasn't requested - is that intentional?"
Stage 2: Correctness
Next, verify the code works correctly.
Checklist:
- Logic is sound
- No obvious bugs
- Error paths are handled
- No unfinished code (TODOs without tickets)
Feedback at this stage:
- "This will throw if
useris null" - "The loop exits early before processing all items"
- "What happens when the API call fails?"
Stage 3: Code Quality
Then, evaluate code quality and maintainability.
Checklist:
- Clear naming
- Reasonable function/method length
- No unnecessary complexity
- Follows project conventions
- Appropriate abstractions
Feedback at this stage:
- "Could you rename
datatouserProfilefor clarity?" - "This function is doing three things - consider splitting"
- "We use camelCase for variables in this project"
Stage 4: Testing
Evaluate test coverage and quality.
Checklist:
- New code has tests
- Tests cover main paths and edge cases
- Tests are readable and maintainable
- Tests don't test implementation details
Feedback at this stage:
- "Please add a test for the error case"
- "This test will break if we change the implementation"
- "Consider using a parameterized test for these cases"
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.
- 3d ago First seen · 178 lines · 112 tokens per session scan A cdedab8780f6
structured-code-review is a skill published in the GitHub repository rohitg00/skillkit (1,477 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 112 tokens to every session and 1,186 once invoked, about $0.0006 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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