RRepoGEO

REPOGEO REPORT · LITE

flingjie/Agent-100-Days

Default branch main · commit 4b64d409 · scanned 6/28/2026, 4:57:35 PM

GitHub: 502 stars · 54 forks

AI VISIBILITY SCORE
23 /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
2 / 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 flingjie/Agent-100-Days, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ["Agent Development", "LLM Engineering", "AI Agents", "Learning Path", "Project Based Learning", "Generative AI", "Prompt Engineering", "RAG", "LangChain", "LangGraph"]
  • highlicense#2
    Add a license file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root containing the text of a standard open-source license, such as the MIT License or Apache-2.0 License.
  • mediumabout#3
    Expand the repository description

    Why:

    CURRENT
    100 天搞定 Agent 开发
    COPY-PASTE FIX
    一条从理解 LLM 本质，到构建可控 Agent 系统的工程化学习路径，帮助开发者避免 Agent 开发中的常见陷阱与工程失控。

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 flingjie/Agent-100-Days
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RAGAS
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RAGAS · recommended 1×
  2. gpt-4 · recommended 1×
  3. gpt-3.5-turbo · recommended 1×
  4. Claude 3 Opus · recommended 1×
  5. Llama 3 · recommended 1×
  • CATEGORY QUERY
    What are common mistakes to avoid when building reliable AI agent systems from scratch?
    you: not recommended
    AI recommended (in order):
    1. RAGAS
    2. gpt-4
    3. gpt-3.5-turbo
    4. Claude 3 Opus
    5. Llama 3

    AI recommended 5 alternatives but never named flingjie/Agent-100-Days. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I design robust and controllable AI agents for real-world business applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Microsoft Semantic Kernel
    3. Haystack
    4. OpenAI Assistants API
    5. Rasa
    6. Weights & Biases
    7. MLflow

    AI recommended 7 alternatives but never named flingjie/Agent-100-Days. 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 flingjie/Agent-100-Days?
    pass
    AI named flingjie/Agent-100-Days explicitly

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

  • If a team adopts flingjie/Agent-100-Days in production, what risks or prerequisites should they evaluate first?
    pass
    AI named flingjie/Agent-100-Days 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 flingjie/Agent-100-Days solve, and who is the primary audience?
    pass
    AI did not name flingjie/Agent-100-Days — 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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flingjie/Agent-100-Days — 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