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Found 34 Skills
Agent Context Isolation
Execute proactive auto-loading: automatically detects and loads agents.md files. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Install and configure ktx, the self-improving context layer that teaches AI agents to query data warehouses accurately with approved metrics, semantic layer, and business knowledge.
Use ktx to build a self-improving context layer that teaches AI agents how to query data warehouses accurately with approved metrics, semantic layers, and business knowledge
Build AI agents with structured access to Sanity content via Context MCP. Covers Studio setup, agent implementation, and advanced patterns like client-side tools and custom rendering.
Interactive session to craft a system prompt for an AI agent powered by Sanity Agent Context MCP.
Use this skill whenever the user wants to work with the Loops CLI from the terminal. This includes installing or updating the CLI, authenticating, storing and selecting API keys, validating credentials, and running commands for contacts, contact properties, lists, events, transactional email, campaigns, email messages, themes, and components. Trigger on phrases like "Loops CLI", "loops auth login", "loops campaigns create", "loops email-messages update", "loops themes list", "loops components get", "loops contacts create", "loops events send", "loops transactional send", "loops api-key", "loops agent-context", "brew install loops-so/tap/loops", or any time the user wants to use Loops from the shell instead of application code.
让 agent zoom out，并给出更广的 context 或更高层 perspective。Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.
Pattern for progressively refining context retrieval to solve the subagent context problem
Audit and prune bloated CLAUDE.md or AGENTS.md context files using evidence-based criteria from research on what actually helps coding agents. Use when a user asks to trim, audit, review, or improve their CLAUDE.md, AGENTS.md, or any repository context file for AI coding agents.
Use when a task involves continuing a project, restoring project context, maintaining file-based project memory, updating current-state summaries, or recording meaningful progress across sessions. Works best for long-horizon, file-based projects and supports research writing, product document collaboration, software project coordination, and broader cross-functional project continuity.
End-of-session documentation workflow that updates README, CHANGELOG, agent context files, and creates session logs. Use when wrapping up a working session, when asked to document session progress, when preparing handoff documentation, or when the user says "wrap up", "end session", "document progress", or "save session".