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-030git 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-030)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-030"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-030/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-030"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-030.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 | $0.00043 | $0.01972 |
| Opus 5.5 | $0.00017 | $0.00789 |
| Sonnet 5.5 | $0.00009 | $0.00394 |
| Haiku 4.5 | $0.00004 | $0.00197 |
Grade A, and why
skill-030 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Socratic Code Review
You are initiating a Socratic code review session. Instead of telling the developer what's wrong, you'll ask probing questions that help them discover issues and articulate their reasoning.
When to Use This Skill
Use Socratic review when:
- You want deeper understanding, not just compliance
- The developer should own the insights (learning > fixing)
- Design decisions need articulation and documentation
- You want to surface hidden assumptions
- The code is complex and needs explanation
- You're mentoring or onboarding
Use traditional review when:
- Time is critical and you need fast feedback
- Issues are obvious and straightforward
- You need a written report for documentation
- The developer explicitly wants direct feedback
Usage
# Basic usage - reviews file with standard depth (7-10 questions)
/socratic-review path/to/file.py
# Quick review - 3-5 focused questions
/socratic-review path/to/file.py --depth=quick
# Deep review - 15-20 comprehensive questions
/socratic-review path/to/file.py --depth=deep
# Review specific function/class
/socratic-review path/to/file.py --focus="function_name"
# Review a directory
/socratic-review src/auth/
# Non-interactive mode (for CI/subprocess - asks all questions, synthesizes without waiting)
/socratic-review path/to/file.py --non-interactive
# Output structured JSON for programmatic processing
/socratic-review path/to/file.py --non-interactive --output=review.json
# Write insights to DECISIONS.md
/socratic-review path/to/file.py --write-decisions
How It Works
1. Context Analysis
First, I'll analyze the code to understand:
- What files/functions are being reviewed
- Complexity level and patterns used
- Areas that warrant deeper questions
2. Question Selection
Based on the code, I'll select questions from six categories:
- Design: Why was this approach chosen?
- Edge Cases: What happens in unusual situations?
- Clarity: How would you explain this?
- Philosophy: Does this follow project principles?
- Failure Modes: What could go wrong?
- Testing: How do you know it works?
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 · 300 lines · 43 tokens per session scan A ebeb774f34f2
skill-030 is a skill published in the GitHub repository legendtkl/agentic-skill-router (6 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 1,972 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.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…