RRepoGEO

REPOGEO REPORT · LITE

sagar-n/deepagents

Default branch main · commit 77523362 · scanned 6/8/2026, 7:06:47 PM

GitHub: 953 stars · 149 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 sagar-n/deepagents, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise 'About' description for the repository

    Why:

    COPY-PASTE FIX
    A production-grade Stock Research Agent (V3) built on LangGraph + LangSmith, featuring real-time observability, agent collaboration, and an interactive Deep Agents UI for financial market analysis.
  • mediumlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository with a standard open-source license, such as MIT or Apache-2.0, to clarify usage terms.

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 sagar-n/deepagents
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 2×
  2. apache/flink · recommended 2×
  3. LangChain · recommended 1×
  4. OpenAI API · recommended 1×
  5. Alpha Vantage API · recommended 1×
  • CATEGORY QUERY
    How can I build an AI agent for financial market analysis and stock research?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI API
    3. Alpha Vantage API
    4. yfinance
    5. Pandas
    6. Scikit-learn
    7. Plotly
    8. Matplotlib
    9. Seaborn

    AI recommended 9 alternatives but never named sagar-n/deepagents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What framework helps develop collaborative AI agents with real-time observability for financial data?
    you: not recommended
    AI recommended (in order):
    1. Ray (ray-project/ray)
    2. Ray Dashboard (ray-project/ray)
    3. Akka (akka/akka)
    4. Akka Management (akka/akka-management)
    5. Akka Telemetry (akka/akka-telemetry)
    6. Apache Flink (apache/flink)
    7. Flink UI (apache/flink)
    8. OpenAI Gym (openai/gym)
    9. Prometheus (prometheus/prometheus)
    10. Grafana (grafana/grafana)
    11. TensorFlow Extended (TFX) (tensorflow/tfx)
    12. TensorBoard (tensorflow/tensorboard)

    AI recommended 12 alternatives but never named sagar-n/deepagents. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 sagar-n/deepagents?
    pass
    AI named sagar-n/deepagents explicitly

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

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

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

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sagar-n/deepagents — 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