RRepoGEO

REPOGEO REPORT · LITE

HumanSignal/Adala

Default branch master · commit d7bc4731 · scanned 5/22/2026, 3:56:54 AM

GitHub: 1,569 stars · 150 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 HumanSignal/Adala, 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
    Strengthen README's opening statement to emphasize Adala's niche

    Why:

    CURRENT
    Adala is an **A**utonomous **DA**ta (**L**abeling) **A**gent framework.
    COPY-PASTE FIX
    Adala is a declarative framework for building reliable, autonomous AI agents specifically designed to automate complex data labeling and processing tasks, leveraging LLMs and ground truth for consistent results.
  • mediumtopics#2
    Add specific topics related to data labeling and processing

    Why:

    CURRENT
    agent, agent-based-framework, agent-oriented-programming, autonomous-agents, gpt-4
    COPY-PASTE FIX
    agent, agent-based-framework, agent-oriented-programming, autonomous-agents, gpt-4, data-labeling, data-processing, llm-agents, ai-agents-for-data
  • lowreadme#3
    Add a 'Comparison with other LLM frameworks' section to README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'Adala vs. General LLM Frameworks,' that explicitly outlines Adala's unique focus on reliable, autonomous agents for data labeling and processing, contrasting it with the broader scope of tools like LangChain or LlamaIndex.

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 HumanSignal/Adala
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. run-llama/llama_index · recommended 1×
  3. deepset-ai/haystack · recommended 1×
  4. Significant-Gravitas/AutoGPT · recommended 1×
  5. yoheinakajima/babyagi · recommended 1×
  • CATEGORY QUERY
    How can I build autonomous agents to automate data labeling and processing tasks effectively?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. AutoGPT (Significant-Gravitas/AutoGPT)
    5. BabyAGI (yoheinakajima/babyagi)
    6. Prefect (PrefectHQ/prefect)
    7. Apache Airflow (apache/airflow)
    8. Label Studio (heartexlabs/label-studio)

    AI recommended 8 alternatives but never named HumanSignal/Adala. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks assist in developing reliable AI agents for data tasks, leveraging LLMs and ground truth?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. DSPy
    6. Guardrails AI
    7. Magentic

    AI recommended 7 alternatives but never named HumanSignal/Adala. 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 HumanSignal/Adala?
    pass
    AI named HumanSignal/Adala explicitly

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

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