全部能力

Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning (YouTube, Reddit, review platforms for GEO), content scoring targets, measurement framework, and content differentiation through original research and first-hand experience. Use when user says "blog strategy", "content strategy", "blog positioning", "what should I blog about", "blog topics", "content pillars", "blog ideation".

Implement GraphRAG patterns combining knowledge graphs with retrieval for complex reasoning. Use this skill when building RAG over interconnected data or needing relationship-aware retrieval. Activate when: GraphRAG, knowledge graph, graph retrieval, entity relationships, Neo4j RAG, graph database, connected data.

Profiles runtime performance with CPU, memory, and I/O metrics. Use when measuring bottlenecks before optimization.

Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go…

Generate a conference poster (article + tcbposter LaTeX → A0/A1 PDF + editable PPTX + SVG) from a compiled paper. Use when user says \"做海报\", \"制作海报\",…

Use when the user asks to generate daily paper digests on a general topic. This skill supports both arXiv and bioRxiv (or either one), then produces structured…

Run Karpathy-style autonomous ML search on a real training repository. Use when the user needs to set up or operate `karpathy/autoresearch`, choose the right run mode (setup, `program.md`, bounded loop, result interpretation, or constrained-hardware adaptation), and preserve the immutable `prepare.py` / 300-second / `val_bpb` contract. Not for prompt evaluation, LLM app observability, or repo-local `SKILL.md` optimization — route those to LangSmith, Promptfoo, Braintrust, or `skill-autoresearch`. Triggers on: autoresearch, autonomous ML experiments, `program.md`, `train.py`, `val_bpb`, overnight GPU loop, fixed eval harness.

Search and summarize papers from ArXiv. Use when the user asks for the latest research, specific topics on ArXiv, or a daily summary of AI papers.

Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and…

Researches best practices and creates documentation (guide, manual, ADR, or research). Use when project needs standards-based documentation for a topic.

Comprehensive Finance API integration skill for real-time and historical financial data analysis, market research, and investment decision-making. Priority use…

Generate conference presentation slides (beamer LaTeX → PDF + editable PPTX) from a compiled paper, with speaker notes and full talk script. Use when user says…

Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is…

Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/. Use when asked to audit doc coverage, sync…

Generate Mermaid diagrams from user requirements. Saves .mmd and .md files to figures/ directory with syntax verification. Supports flowcharts, sequence…

MSW search integration — (1) vector search for API docs and implementation guides via the msw-mcp MCP server (mlua_api_retriever / mlua_document_retriever),…

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results.…

Use when writing or refactoring code, before creating files - enforces separation of pure business logic (Functional Core) from side effects (Imperative Shell)…

Use this skill when crafting LLM prompts, implementing chain-of-thought reasoning, designing few-shot examples, building RAG pipelines, or optimizing prompt performance. Triggers on prompt design, system prompts, few-shot learning, chain-of-thought, prompt chaining, RAG, retrieval-augmented generation, prompt templates, structured output, and any task requiring effective LLM interaction patterns.

Use when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results…