菜单
Describes the agent's personality, current capabilities and its relation to the user. Answers questions like 'Who are you?', 'What can you do for me?".
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Deterministic communication metrics for the mirrored Teams channels. Computes reply-latency distributions, after-hours share, burst/fragmentation index, unanswered blockers, and interruption-cascade depth from data/teams/*/messages.jsonl, and refreshes the hyperscreen dashboard data. Use before making ANY quantitative claim about team communication.
Generate an interactive "application simulator" — a tiny, agent-built React mock of an external app (SAP MD04, a CRM, an ERP form) that the trainee can click through. The trainee's clicks stream back to you via viewerState so you can coach in real time. Each simulator is a single self-contained HTML file under `out/simulators/<app>.simulator.html`. Use this skill when the expert asks for a simulator (often in the context of curriculum topic 4 "Werkzeuge") or when a guest asks "can I practice this somewhere?".
Co-author a new roleplay scenario with an expert. Interview the expert about the persona, topic, hints with point values, and evaluation criteria, draft the JSON, and on confirmation write it to roleplay/<slug>.roleplay.json. Use when the expert invokes "Author a roleplay scenario" from the menu, asks "let me add a customer call to practice", "I want to script a difficult buyer", or equivalent. The scenarios authored here are consumed at runtime by the roleplay-engine skill.
Maintains a project knowledge wiki at wiki/ as the agent's long-term memory, dynamically structured around the mission in wiki/_meta/mission.md. Use whenever the user shares a fact, decision, preference, requirement, or finding worth remembering; whenever the user says "remember this", "add to wiki", "we decided", "save", "note that", or "for the record"; whenever the user asks "what do we know about X", "have we considered Y", "what did we decide", "summarize what we have"; whenever a file in the project codebase contains information relevant to the mission and should be ingested; at the end of a session to consolidate findings; and at session start to load relevant context. Reads index first, deduplicates before writing, tracks provenance, appends history rather than overwriting, and creates stubs for mentioned-but-unresearched topics. Pure markdown, no embeddings, no external network.
Engineering Design Support System. Use this skill whenever the user is doing long-horizon product/engineering design and wants to capture intent, decisions, risks, assumptions, evidence, open questions, or hypotheses; whenever they say 'add a decision', 'propose a hypothesis', 'what did we rule out', 'what changed', 'generate a status report', 'show whitespots', 'sharpen this', 'mission', 'realign', or ask what the project knows; at session start to load mission + state; and as the curator/researcher/synthesizer/critic loops. The mission is the versioned north star; the RDF knowledge graph is the system of record for a typed dependency graph (Concept/Decision/Risk/Assumption/Evidence/OpenQuestion/Gap/Whitespot/Hypothesis/Test); the scrapbook is a projected view; the wiki is synthesized prose; hypotheses run as stateful workflows. Pull-only: never push to the engineer except a critic mission-contradiction.
Use this skill whenever the user wants to take structured notes, collect ideas, organize project requirements, or manage a project notebook — trigger on phrases like 'scrapbook', 'add a note', 'what have we captured', 'notebook', 'show my notes', 'what should I focus on', 'jot this down', or any request to review, prioritize, or organize project items. Reads and writes to the project scrapbook via MCP tools, presenting content as a structured hierarchy with priorities and focus levels.
| name | agent-identity |
| description | Describes the agent's personality, current capabilities and its relation to the user. Answers questions like 'Who are you?', 'What can you do for me?". |
The agent's identity is stored in workspace/.agent/identity.json. There you can find your name and how you interact with the user.
The agent's image is stored in workspace and can be accessed by 
.
Create a HTML structure in your response which looks like an ID card with the avatar image at the right, your name and the information from personality.json.
For complex questions asked by the user try to create mermaid diagrams in the folder workspace//out/about.me
