RRepoGEO

REPOGEO REPORT · LITE

anthropics/anthropic-sdk-go

Default branch main · commit e9e55c19 · scanned 7/1/2026, 2:56:19 AM

GitHub: 1,122 stars · 195 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
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/anthropic-sdk-go, 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
    go, golang, sdk, api-client, anthropic, claude, large-language-models, llm, generative-ai
  • highreadme#2
    Clarify the README's opening sentence to emphasize official status and specific models

    Why:

    CURRENT
    The Claude SDK for Go provides access to the Claude API from Go applications.
    COPY-PASTE FIX
    The official Claude SDK for Go provides idiomatic access to Anthropic's Claude family of large language models from Go applications.
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://platform.claude.com/docs/en/api/sdks/go

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/anthropic-sdk-go
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 1×
  2. sashabaranov/go-openai · recommended 1×
  3. Google Cloud Vertex AI (Generative AI) · recommended 1×
  4. Google Cloud Go client libraries · recommended 1×
  5. Anthropic Claude API · recommended 1×
  • CATEGORY QUERY
    How can I integrate a large language model API into my Go application?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. go-openai (sashabaranov/go-openai)
    3. Google Cloud Vertex AI (Generative AI)
    4. Google Cloud Go client libraries
    5. Anthropic Claude API
    6. anthropic-go (liushuangls/anthropic-go)
    7. Hugging Face Inference API
    8. net/http
    9. Azure OpenAI Service
    10. github.com/cenkalti/backoff/v4 (cenkalti/backoff/v4)

    AI recommended 10 alternatives but never named anthropics/anthropic-sdk-go. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Go library to build AI applications with a focus on responsible language generation.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Go library
    2. Google Cloud Go client library
    3. Anthropic Go library
    4. ONNX Runtime
    5. gorgonia/onnx (gorgonia/onnx)
    6. TensorFlow
    7. tensorflow/tensorflow/go (tensorflow/tensorflow/go)
    8. PyTorch
    9. gorgonia/torch (gorgonia/torch)
    10. go-nlp/nlp (go-nlp/nlp)
    11. gorgonia/gorgonia (gorgonia/gorgonia)

    AI recommended 11 alternatives but never named anthropics/anthropic-sdk-go. 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/anthropic-sdk-go?
    pass
    AI did not name anthropics/anthropic-sdk-go — 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/anthropic-sdk-go in production, what risks or prerequisites should they evaluate first?
    pass
    AI named anthropics/anthropic-sdk-go 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/anthropic-sdk-go solve, and who is the primary audience?
    pass
    AI did not name anthropics/anthropic-sdk-go — 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/anthropic-sdk-go — 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