SkillEffect: Checked Lowering for Memory-Bounded Agent Tools
Agent Skills can specify procedural and resource obligations for tool use, and language models instantiate them as concrete programs. However, when models turn this guidance into code for existing tool interfaces, even a semantically correct program may load an entire input and exceed the memory available to one tool call. We present SkillEffect, a checked-lowering runtime for computations with a recoverable source relation, an audited bounded implementation, and a registered output postcondition. Before granting execution authority, an independent checker rebuilds each proposed lowering from the submitted program and immutable input. Every relation plugin supplies a source recognizer, in...
| Authors | Yinuo Wang, Yiyu Shi |
|---|---|
| Primary category | cs.AI |
| Published | 17 August 2026 |
| Last updated at source | 22 August 2026 |
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