Handbook.md shows that long policy documents do not reliably govern agents
Existing benchmarks rarely test this deployment pattern directly; they measure whether an agent can complete a task, not whether a long, binding policy document actually constrains its behavior over an extended tool-use horizon. We present this http URL, a benchmark of 65 agentic tasks modeled on how enterprise employees follow company handbooks. Tasks span five domains (finance, medical billing, insurance, logistics, and HR) and ten fictional companies.
- ▪Existing benchmarks rarely test this deployment pattern directly; they measure whether an agent can complete a task, not whether a long, binding policy document actually constrains its behavior over an extended tool-use horizon.
- ▪We present this http URL, a benchmark of 65 agentic tasks modeled on how enterprise employees follow company handbooks.
- ▪Tasks span five domains (finance, medical billing, insurance, logistics, and HR) and ten fictional companies.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2607.25398 |
| Publication time | Wed, 29 Jul 2026 13:01:57 +0000 |
| Retrieval time | 2026-07-29T13:28:03.701Z |
| Last seen | 2026-07-29T13:28:03.701Z |
| Headline source | Publisher (no WeSearch rewrite) |
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| Summary source text | contentText |
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| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2607.25398 (cs) [Submitted on 28 Jul 2026] Title:HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following Authors:Liudas Panavas, Sebastian Minus, Bradley Monton, Derek Ray, Suhaas Garre, Sushant Mehta, Edwin Chen View a PDF of the paper titled HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following, by Liudas Panavas and 6 other authors View PDF HTML (experimental) Abstract:Language-model agents are increasingly deployed under standing instructions: a system prompt, a policy file, or a skills document is placed in context, and the agent is trusted to let it govern every action that follows.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.