Submit protein folding tasks to the AlphaFold3 C550 inference platform. Use when the user needs to run AlphaFold3 predictions with pre-prepared JSON input files on the AI4S Kubernetes cluster.
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Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Interview the user relentlessly until you reach a shared understanding. Map this as a design tree: every decision branches into the decisions that hang off it.
Work the tree in rounds. The frontier is every decision whose prerequisites are already settled: the questions you can ask now without guessing at answers you haven't heard yet. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round.
Each question should be formatted like so:
❓ **Q1** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices>
➡️ <your recommended answer>
Each round the user answers reshapes the tree: settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a later round, not this one.
Finding facts is your job, never the user's. When a frontier question needs a fact from the environment (filesystem, tools, etc.), dispatch a sub-agent to find it; don't ask the user for anything you could look up yourself. Don't block on it: a running exploration is an unsettled prerequisite, so only the questions downstream of it wait for the sub-agent to report; ask the rest of the frontier now. The decisions are the user's: put each to them and wait.
The session is done when the frontier is empty: every branch of the design tree visited, nothing left silently assumed. Do not act on it until the user confirms you have reached a shared understanding.
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Submit protein folding tasks to the AlphaFold3 C550 inference platform. Use when the user needs to run AlphaFold3 predictions with pre-prepared JSON input files on the AI4S Kubernetes cluster.
中文简介正在准备中。当前显示原文说明。
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
中文简介正在准备中。当前显示原文说明。
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
中文简介正在准备中。当前显示原文说明。
Parse PDFs, Office files, images, and HTML into Markdown/structured outputs with MinerU. Use when SciForge or Codex needs document parsing/OCR for scientific papers, supplementary files, PDFs, scanned documents, tables, formulas, or URL/local-file parsing through MinerU standard or Agent lightweight APIs.
中文简介正在准备中。当前显示原文说明。
Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.
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Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
中文简介正在准备中。当前显示原文说明。