memory-summary-retrieve
Retrieve memory summaries by ID, project, or recency. Returns structured JSON with compression metrics. Use to access compressed historical context for LLM prompts.
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Retrieve memory summaries by ID, project, or recency. Returns structured JSON with compression metrics. Use to access compressed historical context for LLM prompts.
Intelligent memory search with automatic method selection. Supports semantic (vector), keyword, and recent queries. Includes fallback strategies and optional summary inclusion.
Store and retrieve memories using the BrAIny REST API. Use this skill to persist facts, notes, and messages about the user or conversation. Automatically stores context when the context window is reaching its l...
Index project files for semantic code search. Supports incremental updates, progress tracking, and batch embedding generation.
Manage stories, plans, and tasks in the multi-model orchestrator. Use this skill to create feature requests, generate implementation plans, and execute tasks using different Claude models (Opus, Sonnet, Haiku).
Index project files for semantic code search. Supports incremental updates, progress tracking, and batch embedding generation.
Compress memories into structured summaries using low-cost AI models (Claude Haiku, GPT-4o-mini). Triggers when memory count exceeds 50 or token estimate exceeds 40000. Outputs structured JSON with compression...
Create, edit, and analyze Word documents with formatting, templates, and content generation (Official Anthropic skill)
Create, edit, and analyze PowerPoint presentations with AI-powered slide generation, template management, and content extraction (Official Anthropic skill)
Documentation for the main LLM performance experiments (exps_performance)
Generate new Agent Skills following the open standard specification. Use this when asked to create a new skill, teach Copilot a new capability, or capture domain expertise as a reusable skill.
Developer Relations toolkit for Nostr ecosystem and freedom tech. Use for community building, developer advocacy, conference prep, Shakespeare demos/workshops, and decentralized social evangelism.
Comprehensive administrative support for task management, meeting notes, email drafting, document organization, and staying on track. Use for any organizational, scheduling, or administrative work.
Guide for creating new Claude Code skills following best practices. Use when the user asks to create a new skill, agent capability, or wants to extend Claude's autonomous functionality.
Guide for creating, configuring, and distributing Claude Code plugins with hooks, skills, commands, and MCP servers. Use when user asks to create a plugin, set up hooks, add plugin functionality, create a marke...
Send Slack messages and DMs as yourself directly from Claude Code using your browser session credentials. Extracts the target channel or user and message content directly from natural language prompts. Supports...
Convert AI fluency into throughput by embedding AI into repeatable workflows with triggers, quality gates, and iteration loops that compound over time.
Assess AI fluency proficiency using 5-level certification criteria (A through E) based on demonstrated capabilities across the 4D Framework dimensions.
Select appropriate human-AI collaboration modes: Automation (AI acts independently), Augmentation (AI assists human work), or Agency (AI takes delegated responsibility).
Recognize and avoid 15 common AI fluency anti-patterns that undermine effectiveness: over-reliance, prompt magic thinking, verification theater, and more.
Control AI output through structured specifications: define roles, scope, format, decision rules, and abstraction levels. Prompts become contracts, not requests.
Apply Anthropic's 4D Framework for AI delegation: Delegation (task selection), Description (instructions), Discernment (verification), and Diligence (iteration).
Turn vague intent into solvable structures with explicit objectives, constraints, success criteria, and clear human vs AI responsibility boundaries.
Scale AI fluency beyond individuals through standards, guardrails, audit trails, and organizational policies that maintain quality and accountability.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。