REPOGEO REPORT · LITE

ConardLi/easy-agent

Default branch main · commit cabc5121 · scanned 6/16/2026, 11:17:43 PM

GitHub: 816 stars · 110 forks

AI VISIBILITY SCORE

30 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 0 warn · 1 fail

Objective metadata checks

AI knows your name

3 / 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 ConardLi/easy-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

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

OVERALL DIRECTION

highreadme#1

Emphasize the learning aspect in the README's first paragraph

Why:

CURRENT

An open-source, terminal-native project to fully recreate the Claude Code experience from the ground up. Easy Agent is a long-horizon engineering project focused on rebuilding a complete local agentic coding system in TypeScript and Node.js. The goal is not to publish isolated demos, but to incrementally construct a production-style coding agent with a clean architecture, strong safety boundaries, multi-turn orchestration, local tool execution, and the extensibility required for a full Claude Code-class developer experience.

COPY-PASTE FIX

An open-source, terminal-native project to fully recreate the Claude Code experience from the ground up, designed for anyone to learn how a complete local agentic coding system works. Easy Agent is a long-horizon engineering project focused on rebuilding this system in TypeScript and Node.js, aiming to incrementally construct a production-style coding agent with a clean architecture, strong safety boundaries, multi-turn orchestration, local tool execution, and the extensibility required for a full Claude Code-class developer experience.

mediumlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0) that aligns with the project's goals.

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 ConardLi/easy-agent

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 1×
OpenAI GPT-4 · recommended 1×
GPT-3.5 Turbo · recommended 1×
docker/docker-ce · recommended 1×
jupyter/jupyter_client · recommended 1×

CATEGORY QUERY
How can I build an AI agent for local code generation and execution with robust architecture?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. OpenAI GPT-4
3. GPT-3.5 Turbo
4. Docker (docker/docker-ce)
5. Jupyter Kernel (jupyter/jupyter_client)
6. LlamaIndex (run-llama/llama_index)
7. Llama 3
8. Mixtral
9. CodeLlama
10. Ollama (ollama/ollama)
11. AutoGPT (Significant-Gravitas/AutoGPT)
12. BabyAGI (yoheinakajima/babyagi)
13. `subprocess` module
14. `ast` module
15. Anthropic
16. Microsoft Semantic Kernel (microsoft/semantic-kernel)
17. Azure OpenAI Service
AI recommended 17 alternatives but never named ConardLi/easy-agent. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking an open-source TypeScript framework for building multi-turn AI coding assistants with local tools.
you: not recommended
AI recommended (in order):
1. LangChain.js
2. LlamaIndex.TS
3. Botpress
4. NestJS
5. Fastify
AI recommended 5 alternatives but never named ConardLi/easy-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
fail
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 ConardLi/easy-agent?
pass
AI named ConardLi/easy-agent explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts ConardLi/easy-agent in production, what risks or prerequisites should they evaluate first?
pass
AI named ConardLi/easy-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 ConardLi/easy-agent solve, and who is the primary audience?
pass
AI named ConardLi/easy-agent explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of ConardLi/easy-agent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/ConardLi/easy-agent.svg)](https://repogeo.com/en/r/ConardLi/easy-agent)

HTML

<a href="https://repogeo.com/en/r/ConardLi/easy-agent"><img src="https://repogeo.com/badge/ConardLi/easy-agent.svg" alt="RepoGEO" /></a>

Pro

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ConardLi/easy-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