RRepoGEO

REPOGEO REPORT · LITE

hasaneyldrm/exercises-dataset

Default branch main · commit 225b17d6 · scanned 7/1/2026, 1:38:07 AM

GitHub: 6,705 stars · 803 forks

AI VISIBILITY SCORE
28 /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
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 hasaneyldrm/exercises-dataset, 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
  • highabout#1
    Update the repository description to highlight its use for app backends and multilingual data

    Why:

    CURRENT
    A comprehensive dataset of 433 fitness exercises. Each entry includes name, category, target muscle group, equipment, instructions, thumbnail image, and animation video.
    COPY-PASTE FIX
    A developer setup wizard + structured, multilingual exercise dataset (1,324 exercises) to scaffold fitness app backends (DB schema, API code, LLM prompt) with category, body-part, equipment, target, muscle-group data, and step-by-step instructions in 6 languages.
  • highlicense#2
    Add a LICENSE file to clarify usage rights

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to explicitly state the terms of use for the dataset and code.
  • mediumtopics#3
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    excercises, fitness, fitness-app
    COPY-PASTE FIX
    fitness-data, exercise-dataset, multilingual-data, backend-development, api-data, fitness-api, exercise-instructions

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 hasaneyldrm/exercises-dataset
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ExRx.net
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ExRx.net · recommended 2×
  2. MuscleWiki · recommended 2×
  3. OpenAI Gym · recommended 1×
  4. Kaggle Datasets · recommended 1×
  5. Bodybuilding.com Exercise Database · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive dataset of fitness exercises for my app?
    you: not recommended
    AI recommended (in order):
    1. ExRx.net
    2. OpenAI Gym
    3. Kaggle Datasets
    4. MuscleWiki
    5. Bodybuilding.com Exercise Database
    6. GitHub Repositories

    AI recommended 6 alternatives but never named hasaneyldrm/exercises-dataset. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to get structured exercise data with multilingual instructions for a new fitness backend?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Google Cloud Translation API
    3. DeepL API
    4. ExRx.net
    5. MuscleWiki
    6. ExerciseDB API
    7. Wger.de API

    AI recommended 7 alternatives but never named hasaneyldrm/exercises-dataset. 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 hasaneyldrm/exercises-dataset?
    pass
    AI named hasaneyldrm/exercises-dataset explicitly

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

  • If a team adopts hasaneyldrm/exercises-dataset in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hasaneyldrm/exercises-dataset 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 hasaneyldrm/exercises-dataset solve, and who is the primary audience?
    pass
    AI did not name hasaneyldrm/exercises-dataset — 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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hasaneyldrm/exercises-dataset — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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