Data & AI

Decomposes a decision-complete PRD into a clear, minimal set of user-meaningful features with explicit dependencies, producing a roadmap-ready structure without prioritization, scheduling, or implementation detail.

Find Mozilla telemetry probes and Glean metrics. Use when user asks about: Firefox metrics, Glean probes, telemetry data, accessibility probes, search metrics, or any Mozilla product instrumentation.

Deep dive into memory layout, including strides, C vs Fortran order, and zero-copy view generation via stride tricks. Triggers: strides, C-order, Fortran-order, memory locality, stride_tricks.

Step-by-step procedural guidance for executing the /plan command workflow. Covers Phase 0 (Research), Phase 1 (Design), and Phase 2 (Validation) for implementation planning with constitutional compliance.This skill provides step-by-step procedural guidance for tasks handled bythe planning-agent agent. Use when you need to understand the workflow orexecute tasks that planning-agent would typically handle.Triggered by: [TODO: Add trigger phrases]

GPU monitoring and performance metrics for Ollama inference. Check GPUstatus, VRAM usage, loaded models, and inference performance metricslike tokens per second.

Use when starting a new feature that needs planning - runs brainstorming then creates numbered task folder in _tasks/

Synchronizes Cursor Rules (.mdc files in .cursor/rules/) to CLAUDE.md by generating a Rules section with context-efficient descriptions and usage instructions. Use when setting up Cursor Rules for the first time, after adding or modifying rules, or when the Rules section in CLAUDE.md is missing or outdated.

Instructions for downloading the ai4space repository, useful when the user wants to start working with the lunar base model.

Use when Codex needs semantic web search, news reconnaissance, or citation gathering through the Exa MCP server.

无头模式 AI CLI 调用技能：支持 Gemini/Claude/Codex CLI 的无交互批量调用，包含 YOLO 模式和安全模式。用于批量翻译、代码审查、多模型编排等场景。

Comprehensive guide to phylogenetic tree visualization including matplotlib (Python), ggtree (R), and publication-quality figure generation. Covers rectangular, circular, radial layouts, bootstrap annotations, branch coloring, clade highlighting, and interactive visualizations. Based on best practices from Yulab's Tree Data Book.

Work with markdown-based task lists in .llm/todo.md files. Use when managing tasks, working with todo lists, extracting incomplete tasks, marking tasks complete, or implementing tasks from a task list.

Extract lessons from task failures using Reflector agent, merge insights via Curator pattern, achieving 10% accuracy improvement without context collapse. Use for post-failure analysis, lesson extraction, self-improvement, and building resilience. Analyzes what went wrong and formulates actionable lessons. Triggers on "learn from failure", "analyze mistake", "reflect on error", "post-mortem", "failure analysis", "what went wrong".

Use when you need to plan technical solutions that are scalable, secure, and maintainable.

Use space-based/data-grid architectures to scale high-traffic, stateful workloads across nodes.

Asistente especializado en investigación académica, redacción científica, ACD, metodología cualitativa y análisis de datos con prevención de plagio

Load when working on community engagement, moderation policies, member interactions,or developing community standards. Contains best practices for building inclusive,thriving online communities.

AI security co-pilot for identifying, testing, and fixing vulnerabilities in LLM-powered applications.Use when: (1) Securing LLM applications or agents, (2) Generating security test suites with promptfoo,(3) Testing for prompt injection, jailbreaking, data exfiltration, (4) Hardening system prompts,(5) Compliance mapping for OWASP LLM Top 10, NIST AI RMF, CJIS, SOC2, (6) Threat modeling AI systems,(7) Analyzing security eval results, (8) Research on LLM attack/defense techniques.Triggers: "secure my LLM", "prompt injection", "jailbreak test", "AI security", "red team","system prompt hardening", "LLM vulnerability", "promptfoo", "OWASP LLM", "AI compliance".

Build and integrate production-ready RAG (Retrieval-Augmented Generation) chatbots into documentation sites using OpenAI, Qdrant Cloud, and Neon Postgres. Handles complete stack from backend API to frontend UI integration.

Expert guidance for using the FrontRange CLI (fr command) to manage YAML front matter in text documents. Use when working with front-mattered files, YAML metadata, blog posts, markdown with front matter, or when the user mentions 'fr' commands. Supports reading/writing front matter keys, JMESPath-based searching, bulk operations via piping, directory recursion, and multiple format output (JSON/YAML/plist/CSV).