{
  "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": "2610.09681",
  "title": "Cost-Efficient Theorem Proving via Agent Orchestration in Program Verification",
  "summary": "The method replaces fixed-budget LLM provers and monolithic frontier coding agents with symbolic goal selection over two-level proof graphs plus a metalevel router that prices and dispatches bounded specialist agent invocations. It costs the engineering of a proof-graph infrastructure and routing layer, requires Lean 4 toolchain integration, and depends on third-party API calls whose per-invocation pricing must be tracked. It can fail if routing rules overfit to the evaluated benchmarks, if specialist agents behave differently on out-of-distribution proof obligations, or if the orchestration overhead outweighs savings on small proof workloads.",
  "rationale": "The approach is directly implementable with API access and a single-GPU-free setup, but its cost frontier advantage needs validation on the reader's own verification workload before production adoption.",
  "technique": "Cost-aware agent routing for theorem proving",
  "family": "orquestracao_multiagente",
  "recommendation": "testar",
  "published": "2026-10-07",
  "as_of": "2026-10-18",
  "editorial_status": "indexed",
  "source_url": "https://arxiv.org/abs/2610.09681",
  "independent_implementations": 1,
  "total_implementations": 2,
  "stars": 14,
  "citations": null,
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