llms.txt@docs · git:20261101.31183ca · 2026-11-01 · sha256 6c63e7e8bb6e9641
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# AgentFEM > AI-native finite-element computing for humans and agents. AgentFEM keeps finite-element models readable, structured, inspectable, and operable through ordinary Python and a machine-readable CLI. ## Start - [Human quick start](get_started/) - [AI agent quick start](agents/) - [Engineering guides](guide/) - [Examples](examples/) - [Python API](reference/api/) - [Machine manifest](agentfem.json) - [Installation and platform guide](getting_started/) - [Windows short onboarding](windows_agent_installation/) Installation is agent-assisted: inspect the OS, retain the user's mirror choice, reuse existing environments, and check installation readiness. Stop after reporting version, environment and readiness. Offer a first example; create or run it only when requested. No automatic follow-on tasks. No repository clone is required. On Windows follow the short onboarding route; after one failed stage show one manual action, not a retry loop. Read installation.onboarding in agentfem.json for the shared contract. ## Everyday use For an existing project: read its instructions and case, check, run, inspect. For a result-only request: show the existing result without a new solve. Reuse a healthy environment; doctor is for installation, environment changes or runtime failures. Read only the relevant physics/API references. Use installed capabilities when web documentation describes a newer version. Read task_guidance in agentfem.json for task-specific routing. ## Canonical sources - [Repository](https://github.com/haoming-luo/agentfem) - [Scientific knowledge catalog](https://raw.githubusercontent.com/haoming-luo/agentfem/main/src/agentfem/knowledge/catalog.json) - [AgentFEM skill](agents/skill/) ## Result meaning A completed run supplies a computed result. Provenance verification checks the saved record; engineering acceptance uses relevant convergence, balance and reference evidence. Match the checks to the user's intended use.