RRepoGEO

REPOGEO REPORT · LITE

ianarawjo/ChainForge

Default branch main · commit 7f1f9e7d · scanned 5/14/2026, 7:22:08 PM

GitHub: 2,983 stars · 253 forks

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 ianarawjo/ChainForge, 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
    Reposition README H1/description to emphasize systematic comparison and evaluation

    Why:

    CURRENT
    An open-source visual environment for battle-testing prompts to LLMs.
    COPY-PASTE FIX
    An open-source visual environment for **systematic comparison and evaluation** of LLM prompts and models.
  • mediumtopics#2
    Expand repository topics with more specific keywords

    Why:

    CURRENT
    ai, evaluation, large-language-models, llmops, llms, prompt-engineering
    COPY-PASTE FIX
    ai, evaluation, large-language-models, llmops, llms, prompt-engineering, llm-evaluation, prompt-testing, visual-llm-tools, data-flow-programming
  • mediumreadme#3
    Emphasize core differentiator in README's opening paragraphs

    Why:

    CURRENT
    ChainForge is a data flow prompt engineering environment for analyzing and evaluating LLM responses. It enables rapid-fire, quick-and-dirty comparison of prompts, models, and response quality that goes beyond ad-hoc chatting with individual LLMs.
    COPY-PASTE FIX
    ChainForge is a data flow prompt engineering environment for analyzing and evaluating LLM responses. Its core strength lies in its visual, integrated environment for **data-driven experimentation and comparative evaluation** of LLM prompts, chains, and agents, moving beyond ad-hoc testing to systematic optimization. It enables rapid-fire, quick-and-dirty comparison of prompts, models, and response quality that goes beyond ad-hoc chatting with individual LLMs.

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 ianarawjo/ChainForge
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Weights & Biases (W&B Prompts)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Weights & Biases (W&B Prompts) · recommended 1×
  2. LangChain Playground / LangSmith · recommended 1×
  3. Humanloop · recommended 1×
  4. PromptLayer · recommended 1×
  5. Vellum · recommended 1×
  • CATEGORY QUERY
    How can I visually compare and evaluate multiple LLM prompts and models efficiently?
    you: not recommended
    AI recommended (in order):
    1. Weights & Biases (W&B Prompts)
    2. LangChain Playground / LangSmith
    3. Humanloop
    4. PromptLayer
    5. Vellum
    6. Streamlit
    7. Gradio
    8. Deepchecks

    AI recommended 8 alternatives but never named ianarawjo/ChainForge. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools assist with systematic prompt engineering and LLM response evaluation?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. PromptTools
    3. Ragas
    4. OpenAI Evals

    AI recommended 4 alternatives but never named ianarawjo/ChainForge. 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 ianarawjo/ChainForge?
    pass
    AI named ianarawjo/ChainForge explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of ianarawjo/ChainForge. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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ianarawjo/ChainForge — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite