{
  "schema_version": 1,
  "builder_plan": {
    "scenario": "A workflow needs specialist review, but extra agents may add more cost than useful work.",
    "change": "Test the proposed division of work against a single-agent implementation.",
    "baseline": "One agent with the same tools and an equal total token and time budget.",
    "steps": [
      "Locate the paper's implementation and check its license, model support, data needs, and hardware requirements. Stop here if you cannot obtain the required artifacts.",
      "Save a small set of representative product tasks and expected outcomes. Keep evaluation tasks out of any training or tuning, and choose quality and cost limits before running.",
      "Run the baseline and the proposed change on identical inputs. Keep other settings fixed and repeat paired runs to expose variation.",
      "Save per-task outputs, failures, timings, and all usage costs. Review regressions before expanding the test."
    ],
    "measure": "Accepted outputs, coordination failures, wall-clock time, and total cost across all agents.",
    "decision": "Keep the change only if it meets your preselected quality and latency limits and improves the metric you care about after setup and operating costs. Otherwise retain the baseline. This is an exploration plan, not a validated recommendation."
  },
  "builder_review": null,
  "arxiv_id": "2609.25396",
  "title": "Passes Alone, Fails Together: Benchmarking Semantic Coordination in Parallel LLM-Agent Development",
  "summary": "The work replaces unstructured parallel agent execution (agents patching in isolation) with a lightweight coordination signal: after one agent completes a change, other agents receive a message describing that completed change. The cost is minimal additional context tokens and orchestration logic to collect and propagate change summaries; no extra model, training, or hardware is required. It can fail because the constructed tasks producing 97% interference do not estimate real-world frequency (only 1 of 417 reviewed PR pairs showed interference), so the mitigation's value on a given workload is unproven, and a stale or incomplete summary may not capture semantic dependencies.",
  "rationale": "The coordination-message fix is cheap to implement on a single GPU or API setup, but the paper itself shows real-world interference is rare in reviewed PRs, so the reader should validate its benefit on their own multi-agent workflow rather than assume it is needed.",
  "technique": "Concurrency-summary messaging for parallel coding agents",
  "family": "orquestracao_multiagente",
  "recommendation": "testar",
  "published": "2026-09-21",
  "as_of": "2026-10-18",
  "editorial_status": "indexed",
  "source_url": "https://arxiv.org/abs/2609.25396",
  "independent_implementations": 0,
  "total_implementations": 0,
  "stars": 0,
  "citations": null,
  "claims": [
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      "claim_id": "claim-01",
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    {
      "claim_id": "claim-02",
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      "dimension": "compatibility",
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  "risks": [],
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  "lab_reproductions": [],
  "report_available": false,
  "validation_tier": "unknown",
  "evidence_tier": "unknown",
  "infrastructure_basis": "unknown",
  "equations": [],
  "equations_status": "not_fetched",
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