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    "story_id": "mp-2026-08-29-009",
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    "headline": "The Agent Read the Numbers Before It Drew the Plot",
    "slug": "the-agent-read-the-numbers-before-it-drew-the-plot",
    "dek": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
    "summary": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
    "body_text": "Four evaluated agents benefited substantially from domain context and explored data mainly through numerical console output rather than visualizations. They also performed worse when asked to write a reusable sample-to-label Python program than when submitting predictions directly. The released simulations, trajectories and leaderboard make these behavioral differences auditable.",
    "why_it_matters": "TraceBench generates controlled physical time series so root-cause attribution can be tested against known parameter changes.",
    "limitations": [],
    "importance": 8,
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    "first_published_at": "2026-08-29T09:00:00.000-04:00",
    "modified_at": "2026-08-29T09:00:00.000-04:00",
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    "tags": [
      "agents",
      "root cause analysis",
      "time series"
    ],
    "image_url": null,
    "corrections": []
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  "sources": [
    {
      "source_id": "source-2026-08-29-009",
      "title": "arXiv preprint 2608.27182",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2608.27182",
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      "published_at": "2026-08-27T10:29:13.000-04:00",
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  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "The Agent Read the Numbers Before It Drew the Plot",
    "publisher": "The Machine Press",
    "published_at": "2026-08-29T09:00:00.000-04:00",
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