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launch-your-agent-claude-code

Build, deploy, and iterate Claude Managed Agents from idea to production using Claude Code

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Quellinformationen

Repository
reason-machines/ai-agent-skills
Letzte Quellaktivität
2. Juli 2026 um 01:47
Erkannte Sprache von SKILL.md
Englisch
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
launch-your-agent-claude-code
description
Build, deploy, and iterate Claude Managed Agents from idea to production using Claude Code
triggers
["build a claude managed agent","launch my agent to production","create a scheduled claude agent","interview me about my agent idea","deploy agent to anthropic console","grade and iterate my agent","set up a recurring agent workflow","help me build on claude managed agents"]
# launch-your-agent-claude-code > Skill by [ara.so](https://ara.so) — AI Agent Skills collection. ## Overview **launch-your-agent** is a Claude Code skill that takes you from an agent idea to a live Claude Managed Agent (CMA) in your Anthropic Console. It orchestrates the full lifecycle: interview → scope v0 → launch in your account → grade against success criteria → iterate → schedule (if recurring). You walk away with: - A live managed agent in your Console - Complete build artifacts in `my-agent/` (build sheet, API payloads, eval scaffold, launch script) - A graded initial run - Scheduled deployment (if your task recurs) - A `NEXT-DIRECTIONS.md` with v1/v2 roadmap **Primary Language:** HTML (documentation/templates), with JavaScript/TypeScript for agent logic and shell scripts for deployment. ## Installation ```bash git clone https://github.com/anthropics/launch-your-agent.git cd launch-your-agent claude ``` The skills in `.claude/skills/` are auto-loaded when you run Claude Code inside this directory. ## Prerequisites - **Claude Code** installed and authenticated - **Anthropic API key** for your own account (create at platform.claude.com → API keys) - API key stored in local `.env` file (never committed): ```bash # .env ANTHROPIC_API_KEY=sk-ant-api03-... ``` ## Key Commands ### Main Flow ``` /launch-your-agent ``` Starts the full 4-phase flow: 1. **Interview** – Asks about your use case, inputs, outputs, success criteria, scheduling needs 2. **Stage & Launch** – Generates agent config, creates environment, deploys to your Console 3. **Grade & Iterate** – Runs eval against your success criteria, suggests improvements 4. **Automate** – Sets up scheduled deployment if task is recurring ### Status Check / Close-Out ``` /wrap-up ``` Regenerates overview page, recaps all primitives you built, suggests next 1-2 upgrades. ## Configuration ### CMA Primitives Claude Managed Agents support: - **Agent definition**: System prompt, tools, model (`claude-3-5-sonnet-20241022` or `claude-3-7-sonnet-20250219`) - **Environments**: Isolated runtime contexts (dev/staging/prod) - **Secrets**: API keys, credentials (encrypted at rest) - **Scheduled deployments**: Cron-based recurring runs - **Tool use**: API calls, database queries, file operations Limits (as of documentation): - Max system prompt: ~200k tokens - Tools: Up to 2048 per agent - Secrets: String values only, accessed via tool parameters Reference: `cma-primitives.md` in repo root. ### Interview Mapping The interview phase captures: | Question | Maps to CMA primitive | |----------|----------------------| | What problem does this solve? | Agent system prompt (goals section) | | What inputs does it need? | Tool definitions + environment secrets | | What's a successful output? | Eval criteria + success rubric | | How often should it run? | Scheduled deployment config (cron) | | What should it NOT do? | System prompt (constraints/guardrails) | See `interview-to-config.md` for full mapping. ## Code Examples ### Agent Configuration Shape ```typescript // Generated in my-agent/agent-config.json { "name": "daily-standup-summarizer", "model": "claude-3-5-sonnet-20241022", "system_prompt": "You are a standup summarizer. Each morning, you...", "tools": [ { "name": "fetch_github_prs", "description": "Fetch open PRs from team repos", "input_schema": { "type": "object", "properties": { "repo": { "type": "string" }, "github_token": { "type": "string" } }, "required": ["repo", "github_token"] } } ], "max_tokens": 4096 } ``` ### Launch Script ```bash #!/bin/bash # my-agent/launch.sh set -e source .env # 1. Create agent AGENT_ID=$(curl -s https://api.anthropic.com/v1/agents \ -H "anthropic-version: 2023-06-01" \ -H "x-api-key: $ANTHROPIC_API_KEY" \ -H "content-type: application/json" \ -d @agent-config.json | jq -r '.id') echo "Agent created: $AGENT_ID" # 2. Create environment ENV_ID=$(curl -s https://api.anthropic.com/v1/environments \ -H "anthropic-version: 2023-06-01" \ -H "x-api-key: $ANTHROPIC_API_KEY" \ -d "{\"name\": \"production\", \"agent_id\": \"$AGENT_ID\"}" | jq -r '.id') echo "Environment created: $ENV_ID" # 3. Set secrets curl -s https://api.anthropic.com/v1/environments/$ENV_ID/secrets \ -H "anthropic-version: 2023-06-01" \ -H "x-api-key: $ANTHROPIC_API_KEY" \ -d "{\"key\": \"GITHUB_TOKEN\", \"value\": \"$GITHUB_TOKEN\"}" # 4. Deploy curl -s https://api.anthropic.com/v1/agents/$AGENT_ID/deploy \ -H "anthropic-version: 2023-06-01" \ -H "x-api-key: $ANTHROPIC_API_KEY" \ -d "{\"environment_id\": \"$ENV_ID\"}" echo "Deployed to $ENV_ID" ``` ### Eval Scaffold ```javascript // my-agent/eval.js const Anthropic = require('@anthropic-ai/sdk'); async function gradeRun(runId, successCriteria) { const client = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY, }); // Fetch run output const run = await client.agents.runs.retrieve(runId); const output = run.output; // Grade against criteria const gradePrompt = ` Success criteria: ${successCriteria.join('\n')} Agent output: ${output} Did the agent meet all criteria? Respond with JSON: {"pass": true/false, "feedback": "..."} `; const gradeResponse = await client.messages.create({ model: 'claude-3-5-sonnet-20241022', max_tokens: 1024, messages: [{ role: 'user', content: gradePrompt }], }); return JSON.parse(gradeResponse.content[0].text); } module.exports = { gradeRun }; ``` ### Scheduled Deployment ```json // my-agent/schedule-config.json { "agent_id": "agt_abc123", "environment_id": "env_xyz789", "cron": "0 9 * * 1-5", "timezone": "America/Los_Angeles" } ``` ```bash # Apply schedule curl https://api.anthropic.com/v1/schedules \ -H "anthropic-version: 2023-06-01" \ -H "x-api-key: $ANTHROPIC_API_KEY" \ -d @schedule-config.json ``` ## Common Patterns ### Pattern: Internal Workflow Agent **Use case:** Daily standup summary from GitHub + Slack 1. Interview answers: - Problem: "Summarize team activity each morning" - Inputs: GitHub API token, Slack webhook - Success: "Covers all PRs, mentions blockers, <500 words" - Schedule: "Every weekday at 9am PT" 2. Generated tools: `fetch_github_prs`, `post_slack_message` 3. System prompt includes: goals, tone (concise), constraints (no speculation) 4. Scheduled deployment with cron `0 9 * * 1-5` ### Pattern: Customer-Facing Agent **Use case:** Support ticket triage 1. Interview answers: - Problem: "Categorize incoming tickets, suggest help articles" - Inputs: Zendesk API, knowledge base embeddings - Success: "95% category accuracy, links 2+ relevant articles" - Schedule: "Real-time via webhook" 2. Generated tools: `search_kb`, `update_ticket_tags` 3. System prompt includes: customer empathy guidelines, escalation rules 4. No cron schedule (webhook-triggered) ### Pattern: Data Pipeline Agent **Use case:** Weekly analytics rollup 1. Interview answers: - Problem: "Aggregate usage metrics, detect anomalies" - Inputs: Postgres connection, previous week's baseline - Success: "Flags any >20% change, generates CSV" - Schedule: "Mondays at 6am UTC" 2. Generated tools: `query_db`, `write_csv`, `send_email` 3. System prompt includes: statistical thresholds, alert format 4. Scheduled deployment with cron `0 6 * * 1` ## Troubleshooting ### "API key not found" Ensure `.env` file exists in repo root with: ```bash ANTHROPIC_API_KEY=sk-ant-api03-... ``` **Never** commit `.env` — it's in `.gitignore` by default. ### "Agent creation failed: invalid tool schema" Check `my-agent/agent-config.json`: - `input_schema` must be valid JSON Schema - `required` fields must be present in `properties` - Tool names must be lowercase with underscores ### "Eval keeps failing" Refine success criteria in `my-agent/build-sheet.md`: - Make criteria measurable (e.g., "mentions 3+ PRs" not "comprehensive") - Add edge cases to test set - Iterate system prompt with `/launch-your-agent` (picks up where it left off) ### "Schedule not triggering" Verify: - Cron syntax valid (use https://crontab.guru) - Timezone correct (defaults to UTC) - Environment has required secrets set - Check Console → Agents → Runs for error logs ### "Rate limit hit during launch" CMA API respects standard Anthropic rate limits. If hitting during deploy: - Add `sleep 2` between curl commands in `launch.sh` - Or batch secret creation into single call ## File Structure After Launch ``` my-agent/ ├── build-sheet.md # Interview answers + scoping decisions ├── agent-config.json # Agent definition (system prompt, tools, model) ├── environment-config.json # Environment + secrets references ├── schedule-config.json # Cron schedule (if recurring) ├── launch.sh # Resumable deploy script ├── eval.js # Grading logic ├── OVERVIEW.md # Human-readable status page └── NEXT-DIRECTIONS.md # v1/v2 roadmap .env # API keys (git-ignored) ``` ## API Reference See official docs: https://platform.claude.com/docs/en/managed-agents/overview Key endpoints: - `POST /v1/agents` – Create agent - `POST /v1/environments` – Create environment - `POST /v1/environments/{id}/secrets` – Set secrets - `POST /v1/agents/{id}/deploy` – Deploy to environment - `POST /v1/schedules` – Create cron schedule - `GET /v1/agents/runs/{id}` – Fetch run output ## Additional Resources - `cma-primitives.md` – Full inventory of CMA features and limits - `interview-to-config.md` – Detailed interview → config mapping - `examples-bank.md` – Sourced agent examples and proof points - `ui/` – Example overview page templates ## License Apache 2.0 (see LICENSE in repo root)
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