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agent-launcher-orchestrator

Use when someone wants to build, launch, grade or schedule a Claude Managed Agent in their own Anthropic account ('build me an agent', 'run this nightly'). Reads the session goal, routes with goal_router.py and compiles the loop with loop_compiler.py.

Install / Use

npx skills add LeoYeAI/openclaw-master-skills --skill agent-launcher-orchestrator

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

82/100

Category

Automation

Supported Platforms

Claude Code
Gemini CLI
Cursor
OpenAI Codex

Tags

Our assessment of agent-launcher-orchestrator

agent-launcher-orchestrator scores 82/100 on our quality scale, 2344th of 2,878 Automation skills we index.

Its SKILL.md is 4.5 KB long, well organised into 11 sections with 2 code examples: a solid amount of guidance for an agent.

With 2,149 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
15/15
Adoption
14/20
Freshness
11/15

Maintenance, license and trust

  • The repository was last updated about 4 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 98/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

agent-launcher-orchestrator compared with similar skills

All 4 of these similar skills score higher than agent-launcher-orchestrator; compare them before choosing.

SkillScoreStarsUpdatedFormat
agent-launcher-orchestrator (this skill)by LeoYeAI822.1k4mo agoSKILL.md
Agent-Reachby Panniantong100109.6ktodayCLAUDE.md
Scraplingby D4Vinci10098.8k1d agoMCP Server
rufloby ruvnet10081.1ktodayMCP Server
algorithmic-artby anthropics100177.9k45d agoSKILL.md

Frequently asked questions

How do I install agent-launcher-orchestrator?
Run npx skills add LeoYeAI/openclaw-master-skills --skill agent-launcher-orchestrator. The install tabs above show the steps for each supported agent.
Which AI agents does agent-launcher-orchestrator work with?
It is written for Claude Code, Gemini CLI, Cursor and OpenAI Codex, as a SKILL.md file. Other agents that read the same format can often use it too.
Is agent-launcher-orchestrator safe to use?
It is MIT-licensed and scores 98/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is agent-launcher-orchestrator still maintained?
The repository was last updated about 4 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.

name: agent-launcher-orchestrator description: "Use when someone wants to build, launch, grade or schedule a Claude Managed Agent in their own Anthropic account ('build me an agent', 'run this nightly'). Reads the session goal, routes with goal_router.py and compiles the loop with loop_compiler.py." context: fork license: MIT metadata: version: 2.11.2 author: Alireza Rezvani tags: [claude-managed-agents, cma, agent, launch, orchestrator, session-goal, loop, workflow, cron, outcome, byok] compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]

agent-launcher — Domain Orchestrator

Every session starts with a goal — one sentence for one CMA. This orchestrator reads that goal, routes to the right phase, and compiles the goal into a loop or a workflow. Heavy intake stays in the forked context; the parent gets a digest.

Inspired by Anthropic's launch-your-agent reference skill (Apache-2.0). This is an independent re-implementation; CMA semantics come from ../../references/cma-primitives.md.

The through-line: the session goal

State lives at ./my-agent/goal.json (the user's folder). Manage it with goal_state.py (init / set / status / advance) — it also backs the /cs-goal command and the opt-in SessionStart hook. The goal's phase selects the lane; the phase + recurrence selects the loop shape.

Routing (deterministic)

Run the router, then act on its exit code:

python3 scripts/goal_router.py --out-dir ./my-agent
# exit 0 ROUTE  -> fork to the named phase sub-skill
# exit 3 ASK    -> ask the one printed forcing question, then re-route
# exit 4 REFUSE -> goal too vague; get one sentence, then re-route

| Lane (phase) | Sub-skill | Loop/workflow | |---|---|---| | interview | interview | single-pass workflow | | stage-launch | stage-launch | single-pass workflow | | grade-iterate | grade-iterate | bounded grade→iterate loop | | run-without-you | run-without-you | recurring cron deployment loop | | wrap-up | wrap-up | — |

Compile the loop

python3 scripts/loop_compiler.py \
  --out-dir ./my-agent --max-iterations 5 --cron "0 9 * * *" --timezone Europe/Berlin --nest-outcome

loop_compiler.py emits plan.v1: single-pass, grade-iterate (always with a max_iterations cap 1..20), or cron-loop (optionally nesting a self-grading outcome per firing). See ../../references/loops-and-workflows.md.

Pre-flight gates (hard refusals)

  1. No goal set. If goal.json is missing, run goal_state.py init --goal "..." first. The orchestrator does not guess a goal.
  2. Goal too vague. Router exit 4 — get one sentence naming the one job before routing. Never route on under-3-word goals.
  3. Never make API calls. Emit BYOK curl; the user runs it with their own $ANTHROPIC_API_KEY. No script in this plugin touches the network.
  4. Never print the key. Launch scripts read the key from the environment.

Hand-off contract

After routing, fork to the sub-skill with: the goal string, agent_name, out_dir (./my-agent), and the compiled plan.v1. When the sub-skill returns, goal_state.py advance moves the phase and the parent gets a ≤100-word digest (phase done, artifact paths, loop shape, one next step).

Forcing-question library (walk one at a time; recommend + cite)

  1. "What one job should this agent do end-to-end?" — Recommend: the single most repeated task. Cite: interview-to-config.md (six intake slots). Refuse to route a two-job goal; split into two ./my-agent-*/ folders.
  2. "What kicks it off — you ask it, an event, or a schedule?" — Recommend: on-demand for v0, schedule as the Phase-4 upgrade. Cite: loops-and-workflows.md.
  3. "How would you grade a good run?" — Recommend: 3–5 rubric lines grounded in the output. Cite: cma-primitives.md (outcomes; rubric required).
  4. "Is a real integration ready, or do we mock it in v0?" — Recommend: mock with a schema-true custom tool; wire the MCP server as v1. Cite: interview-to-config.md.
  5. "Should run #10 be smarter than run #1?" — Recommend: attach a memory store only if yes; else skip it. Cite: cma-primitives.md (memory limits + injection risk).

Tools

  • scripts/goal_state.py — own goal.json (init/set/status/advance).
  • scripts/goal_router.py — goal → lane (exit 0 route / 3 ask / 4 refuse).
  • scripts/loop_compiler.py — goal+phase → plan.v1 execution shape.

Related Skills

View on GitHub
GitHub Stars2.1k
CategoryAutomation
Updated3mo ago
Forks325

Languages

Python

Trust signals

98/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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