{
  "$schema": "https://themachinepress.com/schemas/story-v1.schema.json",
  "schema_version": "1.0.0",
  "document_type": "machine_press_story",
  "story": {
    "story_id": "mp-2026-09-27-012",
    "source_story_id": "tmp-story-hexis-compiled-agent-skills",
    "edition_id": "mp-2026-09-27-morning-0080",
    "edition_url": "https://themachinepress.com/edition/2026-09-27",
    "position": 12,
    "story_type": "dispatch",
    "section": "developer-tools",
    "editorial_classification": "editorial",
    "headline": "Compiled Skills Cut Agent Tokens by as Much as 88.9%",
    "slug": "compiled-skills-cut-agent-tokens-by-as-much-as-88-9",
    "dek": "HEXIS turned reusable procedures into extended state machines with static checks and replay.",
    "summary": "HEXIS turned reusable procedures into extended state machines with static checks and replay.",
    "body_text": "HEXIS compiles agent skills into extended finite-state machines whose transitions, guards and tool calls can be inspected before execution. Across four benchmarks and four executors, the authors report a 16.1-point gain over Skill+ReAct. For Qwen3.8-27B, token use fell between 38.4% and 88.9%, while accepted traces could be replayed; the results depend on the tasks and skill library tested.",
    "why_it_matters": "HEXIS turned reusable procedures into extended state machines with static checks and replay.",
    "limitations": [],
    "importance": 9,
    "canonical_url": "https://themachinepress.com/story/mp-2026-09-27-012/compiled-skills-cut-agent-tokens-by-as-much-as-88-9",
    "json_url": "https://themachinepress.com/story/mp-2026-09-27-012.json",
    "first_published_at": "2026-09-27T09:00:00.000-04:00",
    "modified_at": "2026-09-27T09:00:00.000-04:00",
    "content_status": "new",
    "is_carryover": false,
    "carryover_reason": null,
    "key_claims": [
      {
        "claim_id": "claim-mp-2026-09-27-012-001",
        "text": "HEXIS turned reusable procedures into extended state machines with static checks and replay.",
        "source_ids": [
          "source-2026-09-27-012"
        ],
        "qualification": null
      }
    ],
    "source_ids": [
      "source-2026-09-27-012"
    ],
    "tags": [
      "agent skills",
      "state machines",
      "token efficiency"
    ],
    "image_url": null,
    "corrections": []
  },
  "sources": [
    {
      "source_id": "source-2026-09-27-012",
      "title": "arXiv preprint 2609.30123",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2609.30123",
      "canonical_url": "https://arxiv.org/abs/2609.30123",
      "source_type": "primary_research",
      "is_primary_source": true,
      "published_at": "2026-09-24T12:58:18.000-04:00",
      "accessed_at": "2026-09-27T08:26:41.000-04:00",
      "supports_claim_ids": [
        "claim-mp-2026-09-27-012-001"
      ]
    }
  ],
  "corrections": [],
  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
  },
  "cite_this_report": {
    "title": "Compiled Skills Cut Agent Tokens by as Much as 88.9%",
    "publisher": "The Machine Press",
    "published_at": "2026-09-27T09:00:00.000-04:00",
    "canonical_url": "https://themachinepress.com/story/mp-2026-09-27-012/compiled-skills-cut-agent-tokens-by-as-much-as-88-9"
  }
}