RRepoGEO

REPOGEO REPORT · LITE

Nano-Collective/nanocoder

Default branch main · commit 618d81e8 · scanned 6/22/2026, 5:21:43 AM

GitHub: 2,146 stars · 204 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
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 Nano-Collective/nanocoder, 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
    Clarify Nanocoder's technology stack and nature in the README

    Why:

    CURRENT
    An open coding agent for your terminal, built by a community collective rather than a company. Bring your own model, keep your code on your machine, and owe nothing to anyone.
    COPY-PASTE FIX
    An open coding agent for your terminal, built by a community collective rather than a company. Bring your own model, keep your code on your machine, and owe nothing to anyone. Nanocoder is a Node.js command-line interface (CLI) tool, not a Python library, designed for agentic coding directly in your terminal.
  • hightopics#2
    Expand repository topics to improve category visibility

    Why:

    CURRENT
    ai, ai-agents, ai-coding, coding-agents, llm, llm-inference, ollama, openai, openrouter
    COPY-PASTE FIX
    ai, ai-agents, ai-coding, coding-agents, llm, llm-inference, ollama, openai, openrouter, cli-tool, developer-tools, ai-assistant, code-generation, local-llm, typescript, nodejs
  • mediumlicense#3
    Add a clear license statement to the README

    Why:

    COPY-PASTE FIX
    ## License

This project includes a LICENSE file detailing its terms of use. Please refer to the LICENSE file for specific licensing information.

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 Nano-Collective/nanocoder
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Continue
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Continue · recommended 1×
  2. OpenDevin · recommended 1×
  3. Smol-AI · recommended 1×
  4. GPT-Engineer · recommended 1×
  5. Auto-GPT · recommended 1×
  • CATEGORY QUERY
    What are some open-source coding agents that run locally for privacy-focused development?
    you: not recommended
    AI recommended (in order):
    1. Continue
    2. OpenDevin
    3. Smol-AI
    4. GPT-Engineer
    5. Auto-GPT
    6. Code Llama
    7. Ollama
    8. LM Studio
    9. llama.cpp

    AI recommended 9 alternatives but never named Nano-Collective/nanocoder. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a command-line AI coding assistant supporting various LLM providers and local inference.
    you: not recommended
    AI recommended (in order):
    1. Continue.dev (continue-dev/continue)
    2. Ollama (ollama/ollama)
    3. aider (paul-gauthier/aider)
    4. smol-dev (smol-ai/smol-dev)
    5. CodeGPT
    6. ShellGPT (theres-no-ai/sgpt)

    AI recommended 6 alternatives but never named Nano-Collective/nanocoder. 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 Nano-Collective/nanocoder?
    pass
    AI named Nano-Collective/nanocoder explicitly

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

  • If a team adopts Nano-Collective/nanocoder in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Nano-Collective/nanocoder 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 Nano-Collective/nanocoder solve, and who is the primary audience?
    pass
    AI named Nano-Collective/nanocoder explicitly

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

Embed your GEO score

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Nano-Collective/nanocoder — 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