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 legendtkl/agentic-skill-router --skill skill-078git clone --depth 1 https://github.com/legendtkl/agentic-skill-routerWrote 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/legendtkl/agentic-skill-router/skill-078)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-078"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-078/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/legendtkl/agentic-skill-router/skill-078"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-078.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 | $0.00054 | $0.02230 |
| Opus 5.5 | $0.00022 | $0.00892 |
| Sonnet 5.5 | $0.00011 | $0.00446 |
| Haiku 4.5 | $0.00005 | $0.00223 |
Grade A, and why
skill-078 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.
This is a copy
97% identical to review-code — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Workflow
Run a comprehensive, multi-perspective code review on the current branch changes. This skill activates the Review Council and integrates automated security scanning to catch issues before they reach a pull request.
[!CAUTION] Scope boundary: This skill reviews code and commits fixes. It does NOT create pull requests, push to remote, or merge anything. When the review is complete, stop and suggest the user run
/submit-prnext. Do not proceed to PR creation — that is/submit-pr's job.
[!WARNING] Checkpoint protocol. When this workflow reaches a
### CHECKPOINT, you must actively prompt the user for a decision — do not simply present information and continue. Use your agent's interactive prompting mechanism (e.g.,AskUserQuestionin Claude Code) to require an explicit response before proceeding. This prevents queued or in-flight messages from being misinterpreted as approval. If your agent lacks interactive prompting, output the checkpoint content and stop all work until the user explicitly responds.
Step 1: Analyze Current Changes
Identify all changes on the current branch:
- Run
git diff origin/main...HEADto see all changes relative to main - Run
git diffandgit diff --cachedto catch any uncommitted work - Run
git statusto see modified, added, and deleted files
Categorize changed files by layer based on your project's directory structure:
- Frontend: UI components, pages, styles, client-side logic
- Backend: API routes, services, business logic, server-side code
- Database: Schema files, migrations, seed data
- Configuration: Config files, CI/CD, container definitions, environment files
- Documentation: Markdown files, docs directories
- Tests: Test files (
.test.*,.spec.*)
Present a summary of changed files by category to the user.
Step 2: Run Formatting and Lint Checks
Run your project's formatting and lint commands before the council review to catch mechanical issues early. Common examples:
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 · 228 lines · 54 tokens per session scan A 136d1c16aca4
skill-078 is a skill published in the GitHub repository legendtkl/agentic-skill-router (6 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 2,230 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to review-code, differing in 5 lines, and is treated as a copy.
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