RRepoGEO

REPOGEO REPORT · LITE

janhq/ichigo

Default branch main · commit 21c5ad7c · scanned 6/28/2026, 7:56:57 PM

GitHub: 2,487 stars · 149 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
30 /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
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 janhq/ichigo, 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 repo's core purpose as a local voice AI toolkit in the README's opening

    Why:

    COPY-PASTE FIX
    Add the following sentence immediately after the H1: 'Ichigo is a streamlined speech package for developers, providing local, real-time voice AI capabilities including Automatic Speech Recognition (ASR), Speech Language Models (SLM), and upcoming Text-to-Speech (TTS).'
  • hightopics#2
    Add relevant topics to improve categorization and searchability

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    speech-recognition, text-to-speech, voice-ai, llm, local-inference, real-time, python, fastapi, speech-language-model
  • highlicense#3
    Add a LICENSE file to clarify usage rights

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the repository root to clearly state the terms of use.

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 janhq/ichigo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA Riva
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA Riva · recommended 1×
  2. Mozilla DeepSpeech · recommended 1×
  3. Picovoice Rhino Speech-to-Intent · recommended 1×
  4. Coqui STT · recommended 1×
  5. Vosk · recommended 1×
  • CATEGORY QUERY
    Looking for a robust local real-time voice AI toolkit for developer applications.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Riva
    2. Mozilla DeepSpeech
    3. Picovoice Rhino Speech-to-Intent
    4. Coqui STT
    5. Vosk
    6. OpenAI Whisper

    AI recommended 6 alternatives but never named janhq/ichigo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good options for integrating speech recognition and a speech LLM locally?
    you: not recommended
    AI recommended (in order):
    1. Whisper (openai/whisper)
    2. Llama.cpp (ggerganov/llama.cpp)
    3. Silero VAD (snakers4/silero-vad)
    4. Picovoice Rhino (Picovoice/rhino)
    5. Picovoice Porcupine (Picovoice/porcupine)
    6. Mozilla DeepSpeech (mozilla/DeepSpeech)
    7. Coqui STT (coqui-ai/STT)
    8. Vosk (alphacep/vosk-api)

    AI recommended 8 alternatives but never named janhq/ichigo. 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 janhq/ichigo?
    pass
    AI named janhq/ichigo explicitly

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

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

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

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janhq/ichigo — 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