skill-073

skill-073 is a skill for Claude Code, Codex from legendtkl/agentic-skill-router. It costs 25 tokens per session (1,272 once invoked), scanned A, original, MIT.

A worker-agent protocol for systems where a supervisor starts, monitors, and restarts agents. Worker agents report completion, request clarification, or exit when they receive a shutdown message.

In plain words
What is it for?
It helps implement message loops, send completion results through a pipe, handle clarification requests, and define restart and shutdown behavior.
Why use it?
It makes worker behavior and exit conditions explicit, so supervisors can track work and respond consistently when agents finish or stop.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps implement message loops, send completion results through a pipe, handle clarification requests, and define restart and shutdown behavior.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/legendtkl/agentic-skill-router/skill-073
Install

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.

Any agent
npx skills add legendtkl/agentic-skill-router --skill skill-073
Clone the repo
git clone --depth 1 https://github.com/legendtkl/agentic-skill-router

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for skill-073

README.md
[![agentmods](https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-073/github.svg)](https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-073)
Your own site
<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-073"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-073/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.

agentmods 80×15 button for skill-073

Your own site · 80×15
<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-073"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-073.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,272 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00025 $0.01272
Opus 5 $0.00013 $0.00636
Sonnet 5 $0.00005 $0.00254
Haiku 4.5 $0.00003 $0.00127

Measured 6d ago against content hash 0fb8101f161c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

skill-073 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 6d 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.

experiments/dci-compare/skillrouter-skills/skill-073/SKILL.md · 178 lines

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.

Worker Protocol

"Complete work, send message via pipe, exit. Supervisor restarts if needed."

When to Use This Skill

Use when:

  • Implementing worker agent behavior
  • Understanding when/how to exit
  • Understanding supervisor auto-restart

Use proactively:

  • Reference before implementing agent message loops
  • After completing work, before exiting

Quick Start

Connect to watchdog

Connect-ToWatchdog -AgentName "developer" -SessionDir "..claude\session"

Enter message loop

Enter-AgentLoop -MessageHandler { param($Message) switch ($Message.type) { "WorkAssign" { Send-WorkComplete -TaskId $Message.payload.taskId -Result "success" } } }


Example 2: Send work complete
```powershell
Send-WorkComplete -TaskId "feat-001" -Result "success" -Notes "Complete"

Example 3: Exit conditions

  • Work complete → WorkComplete → Exit (code 0)
  • Need clarification → Query → Exit (code 0)
  • Shutdown received → Exit (code 42)
</examples>

---

## Architecture

┌─────────────────────────────────────────────────────────────┐ │ ACTOR SUPERVISOR (Watchdog) │ │ 1. StartActor(agentName) - creates bidirectional pipe │ │ 2. Wait for agent connection via agent-runtime.ps1 │ │ 3. Supervise() - check for crashes, restart with backoff │ │ 4. Route messages between agents via pipes │ │ 5. StopAll() - graceful shutdown │ └───────────────────────────┬───────────────────────────────────┘ │ ┌───────────▼─────────────┐ │ PM ↔ Workers (pipes) │ │ Event Log (source) │ └──────────────────────────┘


---

## Agent Lifecycle

┌─────────────┐ ┌──────────────┐ ┌─────────────┐ │ CONNECT │ ──▶ │ DO WORK │ ──▶ │ EXIT │ │ (agent- │ │ (receive via │ │ (supervisor │ │ runtime) │ │ pipe, │ │ may restart)│ └─────────────┘ │ process) │ └─────────────┘ └──────────────┘


**Key Principle**: Each agent run processes messages, completes work, exits. Supervisor restarts when needed.

---

## Event-Driven vs Sequential Mode

| Aspect | Event-Driven | Sequential |
|--------|-------------|------------|
| Agent spawning | On demand | One at a time |
| Message delivery | Named pipes | Handoff file |
| Parallel work | Yes | No |
| Startup | `/ralph-coordinator-event` | `/ralph-coordinator-single` |
| Connection | `agent-runtime.ps1` | Handoff files |

---

## Exit Conditions

| Condition | Action | Exit Code | Restarted |
|-----------|--------|-----------|-----------|
| Work complete | Send `WorkComplete` | 0 | No (new task will spawn) |
| Need clarification | Send `Query` | 0 | No |
| Blocking issue | Send `WorkBlocked` | 0 | No |
| Shutdown received | - | 42 | No |
| Crash | - | Non-zero | Yes (with backoff) |

**Supervisor restart strategy**:
- Exponential backoff: 5s, 10s, 20s, 40s, 60s (max)
- Max 3 restarts per agent
- Graceful exits (0 or 42) are not restarted

---

## V2 vs V1

| Aspect | V1 (Legacy) | V2 (Current) |
|--------|-------------|--------------|
| Agent lifecycle | File queue monitoring | Pipe-based event loop |
| Delivery latency | 2-5 seconds | <10 milliseconds |
| Crash recovery | Manual health checks | Automatic (ActorSupervisor) |
| State persistence | Multiple files | Single event log |
| Message types | 47+ types | 12 core types |
| Restart strategy | None | Exponential backoff |

---

## Complete Worker Example

```powershell

Read the full file on GitHub · 178 lines

Changes

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.

  1. 6d ago First seen · 178 lines · 25 tokens per session scan A 0fb8101f161c

Subscribe to this mod's changes

skill-073 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 1,272 once invoked, about $0.0001 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 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens