REPOGEO REPORT · LITE

zhimaAi/chatwiki

Default branch main · commit 3fef0913 · scanned 5/31/2026, 1:47:09 AM

GitHub: 1,958 stars · 307 forks

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 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 zhimaAi/chatwiki, 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

Correct typo and add WeChat-specific topics

Why:

CURRENT

agent, ai, aytomation, llm, rag, workflow

COPY-PASTE FIX

agent, ai, automation, llm, rag, workflow, wechat, wechat-official-account, wechat-workflow

highreadme#2

Reinforce WeChat focus in the README's immediate opening

Why:

CURRENT

The current README structure places the core positioning under a '## Product Positioning' heading, after language links.

COPY-PASTE FIX

Add a concise, direct sentence immediately after the language links (e.g., after the `</p>` tag for language links and before any headings), such as: 'ChatWiki is the leading AI agent platform for WeChat Official Accounts, enabling RAG-powered customer service bots and workflow automation.'

mediumlicense#3

Clarify the existing license in the README

Why:

COPY-PASTE FIX

Add a section or line in the README, for example: '## License\nThis project is licensed under the terms outlined in the LICENSE file, which is a custom license combining elements of [mention specific licenses if known, e.g., Apache 2.0 and MIT].'

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 zhimaAi/chatwiki

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Google Cloud Dialogflow CX

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Google Cloud Dialogflow CX · recommended 2×
Azure OpenAI Service · recommended 2×
WeChat Official Account Platform · recommended 1×
OpenAI API · recommended 1×
GPT-4 · recommended 1×

CATEGORY QUERY
How to build an AI agent for WeChat official accounts to automate content and replies?
you: not recommended
AI recommended (in order):
1. WeChat Official Account Platform
2. OpenAI API
3. GPT-4
4. GPT-3.5 Turbo
5. Node.js
6. Python
7. Go
8. Express.js (expressjs/express)
9. Flask (pallets/flask)
10. Django (django/django)
11. Gin (gin-gonic/gin)
12. Google Cloud Dialogflow ES
13. Google Cloud Dialogflow CX
14. Microsoft Azure Bot Service
15. Azure OpenAI Service
16. Azure Functions
17. Azure App Service
18. LangChain (langchain-ai/langchain)
19. Rasa Open Source (RasaHQ/rasa)
20. AWS EC2
21. AWS Lambda
22. Google Cloud Run
23. Google Cloud Functions
24. PostgreSQL
25. MongoDB
26. Redis
AI recommended 26 alternatives but never named zhimaAi/chatwiki. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best platforms for creating RAG-powered AI customer service bots for WeChat workflows?
you: not recommended
AI recommended (in order):
1. LangChain
2. LlamaIndex
3. Rasa Open Source
4. Azure AI Bot Service
5. Azure AI Search
6. Azure OpenAI Service
7. Google Cloud Dialogflow CX
8. Vertex AI Search and Conversation
9. FastAPI
10. Express.js
11. Pinecone
12. Weaviate
AI recommended 12 alternatives but never named zhimaAi/chatwiki. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 zhimaAi/chatwiki?
pass
AI named zhimaAi/chatwiki explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts zhimaAi/chatwiki in production, what risks or prerequisites should they evaluate first?
pass
AI named zhimaAi/chatwiki 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 zhimaAi/chatwiki solve, and who is the primary audience?
pass
AI named zhimaAi/chatwiki 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 zhimaAi/chatwiki. 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/zhimaAi/chatwiki.svg)](https://repogeo.com/en/r/zhimaAi/chatwiki)

HTML

<a href="https://repogeo.com/en/r/zhimaAi/chatwiki"><img src="https://repogeo.com/badge/zhimaAi/chatwiki.svg" alt="RepoGEO" /></a>

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