RRepoGEO

REPOGEO REPORT · LITE

tmc/langchaingo

Default branch main · commit 8fea3de6 · scanned 5/18/2026, 7:16:57 PM

GitHub: 9,257 stars · 1,098 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
33 /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
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 tmc/langchaingo, 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
  • highreadme#1
    Explicitly state the repository's identity as 'LangChain Go' in the README's opening

    Why:

    CURRENT
    ⚡ Building applications with LLMs through composability, with Go! ⚡
    COPY-PASTE FIX
    This repository, `tmc/langchaingo`, is the official Go language implementation of LangChain, enabling Go developers to build powerful applications with Large Language Models through composability.
  • hightopics#2
    Add more specific topics related to LLM orchestration and AI agents

    Why:

    CURRENT
    ai, go, golang, langchain
    COPY-PASTE FIX
    ai, go, golang, langchain, llm, large-language-models, llm-orchestration, ai-agents, generative-ai
  • mediumreadme#3
    Add a 'Key Features' section to highlight the repository's core differentiator

    Why:

    COPY-PASTE FIX
    ## ✨ Key Features

As the primary Go implementation of LangChain, `tmc/langchaingo` offers native Go performance, type safety, and seamless integration for building robust LLM-powered applications in the Go ecosystem. It provides a comprehensive toolkit for creating AI agents, orchestrating complex LLM workflows, and connecting to various models and data sources.

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 tmc/langchaingo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Go-OpenAI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Go-OpenAI · recommended 2×
  2. LangChain Go · recommended 2×
  3. Google Cloud Go Client Libraries · recommended 1×
  4. LocalAI · recommended 1×
  5. Ollama · recommended 1×
  • CATEGORY QUERY
    How can I build large language model applications using the Go programming language?
    you: not recommended
    AI recommended (in order):
    1. Go-OpenAI
    2. Google Cloud Go Client Libraries
    3. LocalAI
    4. Ollama
    5. LangChain Go

    AI recommended 5 alternatives but never named tmc/langchaingo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best Go libraries for developing AI agents and orchestrating LLM workflows?
    you: not recommended
    AI recommended (in order):
    1. LangChain Go
    2. Go-OpenAI
    3. LlamaIndex Go
    4. gollm
    5. Go-Cohere
    6. Go-Google-GenerativeAI

    AI recommended 6 alternatives but never named tmc/langchaingo. 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 tmc/langchaingo?
    pass
    AI did not name tmc/langchaingo — 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 tmc/langchaingo in production, what risks or prerequisites should they evaluate first?
    pass
    AI named tmc/langchaingo 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 tmc/langchaingo solve, and who is the primary audience?
    pass
    AI named tmc/langchaingo explicitly

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

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tmc/langchaingo — 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