RRepoGEO

REPOGEO REPORT · LITE

InternLM/lagent

Default branch main · commit 0ab2e2f5 · scanned 5/23/2026, 10:11:52 AM

GitHub: 2,251 stars · 230 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
35 /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
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 InternLM/lagent, 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
    Add a concise, descriptive opening statement to the README

    Why:

    CURRENT
    The README excerpt begins with badges, followed by 'Installation' and 'Usage' sections.
    COPY-PASTE FIX
    InternLM/lagent is a lightweight, PyTorch-inspired framework for building and deploying interactive, tool-augmented agents powered by Large Language Models (LLMs). It simplifies the creation of multi-agent applications by enabling LLMs to effectively call and utilize tools.
  • highhomepage#2
    Add the project's documentation URL as the homepage

    Why:

    COPY-PASTE FIX
    https://lagent.readthedocs.io/en/latest/
  • mediumtopics#3
    Add more specific topics to reinforce the LLM agent framework category

    Why:

    CURRENT
    agent, gpt, llm, transformers
    COPY-PASTE FIX
    llm-agent, agent-framework, multi-agent, llm, gpt, transformers, agent

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 InternLM/lagent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Haystack
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Haystack · recommended 2×
  2. Rasa Open Source · recommended 1×
  3. DeepPavlov · recommended 1×
  4. OpenNMT-py · recommended 1×
  5. ParlAI · recommended 1×
  • CATEGORY QUERY
    What are the best Python frameworks for developing conversational AI agents?
    you: not recommended
    AI recommended (in order):
    1. Rasa Open Source
    2. Haystack
    3. DeepPavlov
    4. OpenNMT-py
    5. ParlAI
    6. Hugging Face Transformers

    AI recommended 6 alternatives but never named InternLM/lagent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    I need a simple way to create multi-agent applications using large language models.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGen
    3. CrewAI
    4. LlamaIndex
    5. Haystack
    6. Mirascope

    AI recommended 6 alternatives but never named InternLM/lagent. 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 InternLM/lagent?
    pass
    AI named InternLM/lagent explicitly

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

  • If a team adopts InternLM/lagent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named InternLM/lagent 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 InternLM/lagent solve, and who is the primary audience?
    pass
    AI named InternLM/lagent 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 InternLM/lagent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/InternLM/lagent.svg)](https://repogeo.com/en/r/InternLM/lagent)
HTML
<a href="https://repogeo.com/en/r/InternLM/lagent"><img src="https://repogeo.com/badge/InternLM/lagent.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

InternLM/lagent — 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