CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents

CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents | Signal Canvas | ScienceToStartup

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Proof freshness: stale
Proof status: verified
Display score: 6/10
Last proof check: 2026-03-19
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 50%

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Canonical ID codescout-an-effective-recipe-for-reinforcement-learning-of-code-search-agents | Route /signal-canvas/codescout-an-effective-recipe-for-reinforcement-learning-of-code-search-agents

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/codescout-an-effective-recipe-for-reinforcement-learning-of-code-search-agents

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "codescout-an-effective-recipe-for-reinforcement-learning-of-code-search-agents",
    "query_text": "Summarize CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents"
  }
}

source_context

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  "query": "CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents",
  "normalized_query": "2603.17829",
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  "paper_ref": "codescout-an-effective-recipe-for-reinforcement-learning-of-code-search-agents",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 0

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents

PDF: https://arxiv.org/pdf/2603.17829v1

Repository: https://github.com/OpenHands/codescout

Source count: Pending verification

Coverage: 50%

Last proof check: 2026-03-19T21:58:08.026Z

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CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents

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