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 leechen298/Code2Skill --skill code2skill-review-sourcegit clone --depth 1 https://github.com/leechen298/Code2SkillWrote 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/leechen298/code2skill/code2skill-review-source)<a href="https://agentmods.dev/skills/leechen298/code2skill/code2skill-review-source"><img src="https://agentmods.dev/badge/skills/leechen298/code2skill/code2skill-review-source/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/leechen298/code2skill/code2skill-review-source"><img src="https://agentmods.dev/badge/skills/leechen298/code2skill/code2skill-review-source.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.02835 |
| Opus 5.5 | $0.00021 | $0.01134 |
| Sonnet 5.5 | $0.00010 | $0.00567 |
| Haiku 4.5 | $0.00005 | $0.00283 |
Grade A, and why
code2skill-review-source 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code2Skill Source Review
Review whether the request semantics in an existing Code2Skill-generated result match the authorized source code. This Skill answers "how closely does the generated result match the source code?" It does not re-inventory all major goals, and it does not treat the generated result's own passing tests as evidence of correctness.
The complete Chinese version is available at references/SKILL.zh-CN.md. Follow the user's language for final replies, review conclusions, and all user-facing content.
If you first need to determine whether the major goals are complete and whether the standard paths can be completed, use code2skill-review-flow. The two Reviews can run separately and do not depend on each other.
This Skill is read-only, offline, and source-first by default. It is not a second heavyweight audit process. It returns only concise, actionable findings and does not generate a Canonical Contract, evidence matrix, review report, or other deliverable files.
Inputs and boundaries
Before starting, identify:
- the path to the generated package under review;
- the source roots explicitly authorized by the user;
- the Skill, major goal, Tool, or capability scope under review;
- whether the user has also authorized fixes; remain read-only unless this authorization is explicit.
Review only the default output of code2skill-generate. If you encounter an advanced-validation format, a legacy version, or an unrecognized directory, explain that this process does not apply rather than forcing it onto the artifact.
Search only the authorized source roots. When a client or Consumer exists, focus on the business invocation it actually triggers and the final invocation construction. When no client exists, begin from the public API, RPC, Service, message, or task entry point specified by the user. When necessary, verify public Request/Response definitions, service/method identity, message destination/key, task payload, authentication headers, or upload interfaces, but do not descend into backend Services, databases, downstream message processing, approvals, or complete business validation.
What ships with it
2 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.
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 · 189 lines · 52 tokens per session scan A 731c0565a275
code2skill-review-source is a skill published in the GitHub repository leechen298/Code2Skill (9 stars, last pushed 10d ago), licensed MIT. It adds 52 tokens to every session and 2,835 once invoked, about $0.0002 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.
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code-review-zh
A Git-based code review workflow that compares changes from a chosen commit, branch, tag, or merge point. It checks both whether the code follows the repository's written standards and whether it implements the requested specification.
improve-codebase-architecture-zh
A codebase architecture review that scans for modules that hide useful complexity poorly, then produces a visual HTML report and discusses one selected finding in depth.