RRepoGEO

REPOGEO REPORT · LITE

agentjido/req_llm

Default branch main · commit ffa7ba38 · scanned 6/11/2026, 3:46:50 AM

GitHub: 532 stars · 163 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 agentjido/req_llm, 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's opening to emphasize unified multi-provider API

    Why:

    CURRENT
    A Req- and Finch-backed package to call LLM APIs that standardizes requests and responses across providers.
    COPY-PASTE FIX
    ReqLLM is a **unified, multi-provider Elixir library** for interacting with Large Language Model (LLM) APIs, built on Req and Finch. It provides a standardized, idiomatic Elixir interface for requests and responses across various providers.
  • mediumtopics#2
    Add specific topics for unified multi-provider LLM API clients

    Why:

    CURRENT
    ai, ai-providers, elixir, elixir-package, llm, req
    COPY-PASTE FIX
    ai, ai-providers, elixir, elixir-package, llm, req, llm-api-client, multi-provider, unified-api
  • mediumabout#3
    Update repository description to highlight unified multi-provider nature

    Why:

    CURRENT
    Composable Elixir library for LLM interactions built on Req and Finch
    COPY-PASTE FIX
    Composable Elixir library for unified, multi-provider LLM interactions, built on Req and Finch.

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 agentjido/req_llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI · recommended 2×
  2. Finch · recommended 2×
  3. HTTPoison · recommended 2×
  4. llm · recommended 1×
  5. LangChain.ex · recommended 1×
  • CATEGORY QUERY
    How to simplify calling various LLM APIs consistently in an Elixir application?
    you: not recommended
    AI recommended (in order):
    1. llm
    2. OpenAI
    3. Finch
    4. HTTPoison
    5. LangChain.ex
    6. Req

    AI recommended 6 alternatives but never named agentjido/req_llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Elixir library for unified large language model API interaction across multiple providers.
    you: not recommended
    AI recommended (in order):
    1. ex_llm
    2. OpenAI
    3. ex_anthropic
    4. ex_google_gemini
    5. Finch
    6. HTTPoison

    AI recommended 6 alternatives but never named agentjido/req_llm. 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 agentjido/req_llm?
    pass
    AI named agentjido/req_llm explicitly

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

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

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

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agentjido/req_llm — 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