RRepoGEO

REPOGEO REPORT · LITE

langwatch/better-agents

Default branch main · commit 00c44b92 · scanned 6/21/2026, 4:11:50 PM

GitHub: 1,537 stars · 152 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 langwatch/better-agents, 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 opening to highlight production-readiness, testing, and observability

    Why:

    CURRENT
    Better Agents is a CLI tool and a set of standards for agent building. It supercharges your coding assistant (Kilocode, Claude Code, Cursor, etc), making it an expert in any agent framework you choose (Agno, Mastra, LangGraph etc) and all their best practices.
    COPY-PASTE FIX
    Better Agents is a CLI tool and a set of standards for building production-ready, robust, and reliable AI agents. It provides the structure, testing, and observability tools needed to ensure your agents proactively handle common failure modes (e.g., hallucinations, loops, tool errors, context limits), making it the best way to start any new agent project with industry best practices.
  • mediumreadme#2
    Add a 'Comparison' section to clarify how Better Agents complements or differs from frameworks and observability tools

    Why:

    COPY-PASTE FIX
    ## Comparison to Other Tools
Better Agents is not another LLM agent framework like LangChain or LlamaIndex. Instead, it's a meta-framework and CLI tool designed to provide the structure, best practices, and tooling (for testing, evaluation, and and observability) to build production-ready agents *using* any framework you choose. While tools like LangSmith, Phoenix, or Helicone offer specific observability features, Better Agents integrates these concerns from the ground up, ensuring your agent projects are robust and reliable from day one, proactively handling common failure modes like hallucinations, loops, and tool errors.
  • lowtopics#3
    Add 'observability' to the repository topics

    Why:

    CURRENT
    agent-framework, agent-testing, ai-agents, cli, dev-tool, lllm, llmops, mcp, python, typescript
    COPY-PASTE FIX
    agent-framework, agent-testing, ai-agents, cli, dev-tool, lllm, llmops, mcp, python, typescript, observability

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 langwatch/better-agents
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangSmith
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangSmith · recommended 2×
  2. LangChain · recommended 1×
  3. LlamaIndex · recommended 1×
  4. OpenAI API · recommended 1×
  5. Azure OpenAI Service · recommended 1×
  • CATEGORY QUERY
    How to start an AI agent project with best practices and robust testing?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI API
    4. Azure OpenAI Service
    5. LiteLLM
    6. Pytest
    7. Jest
    8. LangSmith
    9. Weights & Biases

    AI recommended 9 alternatives but never named langwatch/better-agents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What development tools help manage, test, and observe LLM agent performance?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LangSmith
    3. Phoenix (Arize-AI/phoenix)
    4. W&B Prompts (wandb/wandb)
    5. Helicone (Helicone/helicone)
    6. DeepEval (confident-ai/deepeval)
    7. OpenReplay (openreplay/openreplay)
    8. MLflow (mlflow/mlflow)

    AI recommended 8 alternatives but never named langwatch/better-agents. 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 langwatch/better-agents?
    pass
    AI named langwatch/better-agents explicitly

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

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

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

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langwatch/better-agents — 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