RRepoGEO

REPOGEO REPORT · LITE

guy-hartstein/company-research-agent

Default branch main · commit 200383d0 · scanned 5/19/2026, 12:28:14 AM

GitHub: 1,890 stars · 274 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
33 /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
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 guy-hartstein/company-research-agent, 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 the README's opening paragraph to clarify its application nature and target audience

    Why:

    CURRENT
    A multi-agent tool that generates comprehensive company research reports. The platform uses a pipeline of AI agents to gather, curate, and synthesize information about any company.
    COPY-PASTE FIX
    An advanced AI-powered application designed for investors, business analysts, and market researchers to generate comprehensive company research reports. This multi-agent tool leverages a pipeline of specialized AI agents to gather, curate, and synthesize deep diligence on any company.
  • mediumtopics#2
    Add more specific domain-related topics to improve categorization

    Why:

    CURRENT
    agents, ai, company, financial-analysis, gemini, gemini-3-flash, langchain, langgraph-python, multi-agent-systems, openai, python, research, tavily, tavily-api, tavily-search
    COPY-PASTE FIX
    agents, ai, company, financial-analysis, gemini, gemini-3-flash, langchain, langgraph-python, multi-agent-systems, openai, python, research, tavily, tavily-api, tavily-search, investment-research, market-intelligence, business-intelligence, due-diligence
  • lowreadme#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Comparison to Alternatives' or 'How is this different?' to the README. This section should clarify that `company-research-agent` is an *application* for *specific company research*, distinguishing it from general AI agent *frameworks* (like LangChain Agents or CrewAI) and raw financial *data terminals* (like Bloomberg Terminal), emphasizing its focus on automated, synthesized reports.

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 guy-hartstein/company-research-agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Bloomberg Terminal
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Bloomberg Terminal · recommended 1×
  2. Refinitiv Eikon (with Workspace) · recommended 1×
  3. S&P Capital IQ · recommended 1×
  4. FactSet · recommended 1×
  5. PitchBook · recommended 1×
  • CATEGORY QUERY
    How to automate comprehensive financial and market research for potential business investments?
    you: not recommended
    AI recommended (in order):
    1. Bloomberg Terminal
    2. Refinitiv Eikon (with Workspace)
    3. S&P Capital IQ
    4. FactSet
    5. PitchBook
    6. AlphaSense
    7. Quandl (now Nasdaq Data Link)

    AI recommended 7 alternatives but never named guy-hartstein/company-research-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best multi-agent AI systems for deep business intelligence and information synthesis?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT (Significant-Gravitas/AutoGPT)
    2. BabyAGI (yoheinakajima/babyagi)
    3. LangChain Agents (langchain-ai/langchain)
    4. CrewAI (joaomdmoura/crewai)
    5. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    6. Hugging Face Agents
    7. Cognosys.ai

    AI recommended 7 alternatives but never named guy-hartstein/company-research-agent. 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 guy-hartstein/company-research-agent?
    pass
    AI named guy-hartstein/company-research-agent explicitly

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

  • If a team adopts guy-hartstein/company-research-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named guy-hartstein/company-research-agent 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 guy-hartstein/company-research-agent solve, and who is the primary audience?
    pass
    AI did not name guy-hartstein/company-research-agent — 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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guy-hartstein/company-research-agent — 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