Story · arXiv

SIGIL: Compiling Agent Skills into Typed Harnesses (arXiv)

paper · Story page

A scribbled handwritten page feeds into a funnel; a neat flowchart of five boxes, one drawn with a dotted outline, comes out the other side.

A SKILL.md is prose the model interprets at runtime, so a required tool call or ordering check can be skipped even when the skill spells it out. SIGIL compiles skills into typed executable programs and leaves semantic choices to the model; across 33 public skills and three runtime models it raised the share of applicable requirements satisfied from 66.0% to 88.6% and cut runtime tokens 2.40-5.95x.

In plain words

  • Researchers turned written instructions for action-taking artificial intelligence systems into programs that computers can follow directly.
  • The process identifies required tools, step order, information flow, and checks before creating code that follows those rules.
  • It still lets the artificial intelligence system decide questions that require interpreting meaning.
  • Across 33 public instruction files and three artificial intelligence systems, the share of applicable requirements completed rose from 66.0% to 88.6%.
  • Teams could make automated work more reliable without removing judgment from choices that depend on meaning.

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