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Found 156 Skills
An agent that helps relationship managers prepare for upcoming client meetings by synthesizing a tailored Point of View and detailed Speaker Notes from multiple information sources.
写入知识文件并自动更新 topics.md 索引
A team of 10 AI agents that manage your Obsidian vault for knowledge, nutrition, and mental wellness using Claude Code
LLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model)
Progressive Domain Crystallization (PDC) — a skill for building and maintaining a living domain knowledge base for any custom business application. Use this skill whenever the user is developing a business application and wants the AI to accumulate understanding of internal terminology, entities, relationships, and business rules over time — especially when that knowledge is not fully defined upfront and grows across sessions. Trigger on any of: "remember how our system works", "learn our domain", "track business entities", "build domain knowledge", "understand our terminology", "grow AI context over time", "domain model", "business rules documentation", or whenever a user says the AI doesn't understand their business-specific language or data model. Also use at the start of any session where a DOMAIN.md file exists in the project — always read it before doing any work.
Fetch a URL and distill its content into the Obsidian wiki. If invoked from inside a project directory, the page lands directly in that project's folder (creating the project in the vault if needed). Otherwise it goes to misc/ and gains project affinity over time. Use this skill when the user says "/ingest-url <url>", "add this URL to the wiki", "ingest this link", "save this page", or pastes a URL and says "add this" or "save this to my wiki".
Brain knowledge base operations. The core read/write cycle: brain-first lookup, read-enrich-write loop, source attribution, ambient enrichment, back-linking. Read this before any brain interaction.
Papyrs integration. Manage Organizations. Use when the user wants to interact with Papyrs data.
Manages cross-session knowledge persistence. Triggers on "remember", "recall", "what did we", "save this decision", "todo", or session handoff.
Used when you need to perform Discover (reverse engineering) on legacy projects with existing code, consolidate repository facts into `.aisdlc/project/`, and you find that AI or teams frequently guess entry points and boundaries, have duplicate writing of indexes and details, or lack evidence chains leading to repeated rework.
Capture corrections, insights, and patterns as reusable project knowledge. Routes learnings to the right instruction file. Applies kaizen: small improvements, error-proofing, standards work. Auto-invoked when a correction pattern is detected 3+ times. Also use manually when Claude makes a repeated mistake, discovers a non-obvious gotcha, or when you want to persist a workflow preference.
Update documentation based on lessons learned. Use after completing work to capture learnings and prevent future issues.