RRepoGEO

REPOGEO REPORT · LITE

anthropics/launch-your-agent

Default branch main · commit 05e9627d · scanned 6/28/2026, 12:12:42 AM

GitHub: 534 stars · 108 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface anthropics/launch-your-agent, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    claude-code, claude-managed-agents, ai-agent-deployment, founder-tools, workflow-automation, anthropic
  • highreadme#2
    Clarify README's opening to prevent miscategorization

    Why:

    CURRENT
    # launch-your-agent
    
    A Claude Code skill that helps a technical founder build whatever they want on **Claude Managed Agents (CMA)** — an internal worker, a piece of their product, a customer-facing agent. It interviews you about what you want to build, scopes a v0, launches it in your own account, grades it against your own definition of done, iterates, and (if it should run on a clock) puts it on a scheduled deployment — with everything bigger laid out as an explicit v1/v2 plan.
    
    > Reference implementation. Not maintained and not accepting contributions. Licensed under [Apache 2.0](./LICENSE).
    COPY-PASTE FIX
    # launch-your-agent: A Guided Workflow for Claude Managed Agents
    
    This repository provides a **Claude Code skill** designed specifically for technical founders to rapidly build, launch, and iterate on **Claude Managed Agents (CMA)**. Unlike general-purpose LLM frameworks, `launch-your-agent` offers a structured, interactive workflow to take your idea from concept to a live, graded, and optionally scheduled agent within your own Anthropic account. It's a reference implementation to demonstrate best practices for CMA development, not a general-purpose agent framework. (Note: This project is not actively maintained and does not accept contributions.)
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://www.anthropic.com/claude-code

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface anthropics/launch-your-agent
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Microsoft Semantic Kernel · recommended 2×
  4. AutoGPT · recommended 2×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    How to build and deploy an AI agent from scratch with structured guidance?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Assistants API
    5. Microsoft Semantic Kernel
    6. AutoGPT
    7. BabyAGI
    8. Hugging Face Transformers Agents

    AI recommended 8 alternatives but never named anthropics/launch-your-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to help technical founders design, launch, and iterate on autonomous AI workers?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGPT
    3. LlamaIndex
    4. OpenAI API
    5. Hugging Face Transformers & Agents
    6. CrewAI
    7. Microsoft Semantic Kernel

    AI recommended 7 alternatives but never named anthropics/launch-your-agent. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of anthropics/launch-your-agent?
    pass
    AI did not name anthropics/launch-your-agent — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts anthropics/launch-your-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named anthropics/launch-your-agent explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo anthropics/launch-your-agent solve, and who is the primary audience?
    pass
    AI did not name anthropics/launch-your-agent — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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anthropics/launch-your-agent — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite