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 lfyxhappy/lfcode --skill api-reviewergit clone --depth 1 https://github.com/lfyxhappy/lfcodeWrote 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/lfyxhappy/lfcode/api-reviewer)<a href="https://agentmods.dev/skills/lfyxhappy/lfcode/api-reviewer"><img src="https://agentmods.dev/badge/skills/lfyxhappy/lfcode/api-reviewer.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 | $0.00053 | $0.00330 |
| Opus 5 | $0.00026 | $0.00165 |
| Sonnet 5 | $0.00011 | $0.00066 |
| Haiku 4.5 | $0.00005 | $0.00033 |
Grade A, and why
api-reviewer 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 yesterday.
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.
What it actually says
API Reviewer
Review an interface as a contract shared by callers, operators, and persisted data.
Workflow
- Locate the route or exported operation, schema definitions, authentication and permission checks, serializers, errors, documentation, and tests.
- Trace representative callers and generated or handwritten clients. Record current method, path or operation name, input, output, status or error behavior, ordering, and limits.
- Check validation, defaults, pagination, idempotency, retries, versioning, backward compatibility, sensitive fields, and observability.
- Separate a review finding from an implementation recommendation. For a requested change, update the narrow contract and its consumers together.
- Add focused contract tests for success, invalid input, authorization, not-found, conflict, and failure paths that apply.
- Verify the real request and response or generated artifact when possible, then run package typecheck and build checks for shared interfaces.
Boundaries
- Do not silently change public names, wire formats, status codes, or authorization semantics.
- Do not call live endpoints with real secrets or destructive payloads unless the target and authorization are explicit.
- Never include credentials or unredacted user data in examples, logs, or documentation.
Completion check
Report compatibility impact, affected consumers, tests, and any contract behavior that could not be exercised.
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.
- yesterday First seen · 28 lines · 53 tokens per session scan A 75a652180bf2
api-reviewer is a skill published in the GitHub repository lfyxhappy/lfcode (2 stars, last pushed 4d ago), licensed MIT. It adds 53 tokens to every session and 330 once invoked, about $0.0003 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 2026-09-05.
Other skills, from other repositories
dcc-orchestration
Orchestrate Codex subagents for complex multi-part coding work. Use when independent exploration, review, tests, or bounded implementation streams can run in parallel; do not use for small sequential tasks or tightly coupled concurrent edits.
Implement (multi-agent loop)
Orchestrate an implement -> review -> fix loop with subagents until reviewers sign off.
Review a GitHub PR (via gh)
Review a specific GitHub pull request with gh — fetch the diff, fan out reviewers, consolidate, and optionally post the review. Requires the gh CLI or the GitHub MCP server.
Design doc (write -> review loop)
Draft a design document and iterate writer/reviewer subagents until consensus.
Review changes (multi-agent)
Delegate read-only reviewers over the local changes/branch and consolidate findings.
code-review
A review process for a pull request, which is a proposed set of code changes. It examines the changed code and its surrounding files for bugs, security problems, design issues, and lint errors.