RRepoGEO

REPOGEO REPORT · LITE

declare-lab/tango

Default branch master · commit 34ecd388 · scanned 6/28/2026, 10:42:48 PM

GitHub: 1,237 stars · 105 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 declare-lab/tango, 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
    Insert a clear introductory sentence about Tango's core purpose

    Why:

    COPY-PASTE FIX
    This repository hosts the models and code for Tango, a state-of-the-art family of diffusion models for text-to-audio generation, leveraging LLM guidance and DPO-based alignment to produce high-quality audio from text prompts.
  • mediumlicense#2
    Clarify the project's license(s) in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is released under [Specify License Name(s) here, e.g., a custom research license, or a combination of licenses like Apache 2.0 for code and CC BY-NC-SA for models/data]. Please refer to the `LICENSE` file for full details.
  • lowreadme#3
    Add a 'Why Tango?' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ## Why Tango?
Tango stands out by [briefly explain unique features, e.g., its LLM-guided approach, DPO alignment, speed (TangoFlux), or specific audio quality/diversity]. Unlike [competitor X], Tango focuses on [specific benefit].

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 declare-lab/tango
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Meta AudioCraft
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Meta AudioCraft · recommended 2×
  2. MusicGen · recommended 1×
  3. AudioGen · recommended 1×
  4. Google AudioLM · recommended 1×
  5. Riffusion · recommended 1×
  • CATEGORY QUERY
    What are the leading open-source models for generating audio content from text descriptions?
    you: not recommended
    AI recommended (in order):
    1. Meta AudioCraft
    2. MusicGen
    3. AudioGen
    4. Google AudioLM
    5. Riffusion
    6. Bark
    7. Tortoise-TTS
    8. OpenAI Jukebox

    AI recommended 8 alternatives but never named declare-lab/tango. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I create realistic soundscapes and speech quickly using text prompts?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Meta AudioCraft
    3. Google Lyra
    4. Descript
    5. Aflorithmic
    6. Replica Studios

    AI recommended 6 alternatives but never named declare-lab/tango. 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 declare-lab/tango?
    pass
    AI named declare-lab/tango explicitly

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

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

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

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Pro

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declare-lab/tango — 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