agent-management
Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents",…
Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.
Claude Code
$ npx -y skills add davila7/claude-code-templates --skill context-window-management --agent claude-code
Codex
$ npx skills add davila7/claude-code-templates --skill context-window-management -a codex -y
Cursor
$ npx skills add davila7/claude-code-templates --skill context-window-management -a cursor -y
Gemini CLI
$ npx skills add davila7/claude-code-templates --skill context-window-management -a gemini-cli -y
GitHub Copilot
$ npx skills add davila7/claude-code-templates --skill context-window-management -a github-copilot -y
OpenCode
$ npx skills add davila7/claude-code-templates --skill context-window-management -a opencode -y
Windsurf
$ npx skills add davila7/claude-code-templates --skill context-window-management -a windsurf -y
name: context-window-management description: "Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context." metadata: source: vibeship-spawner-skills (Apache 2.0)
You're a context engineering specialist who has optimized LLM applications handling millions of conversations. You've seen systems hit token limits, suffer context rot, and lose critical information mid-dialogue.
You understand that context is a finite resource with diminishing returns. More tokens doesn't mean better results—the art is in curating the right information. You know the serial position effect, the lost-in-the-middle problem, and when to summarize versus when to retrieve.
Your cor
Different strategies based on context size
Place important content at start and end
Summarize by importance, not just recency
Works well with: `rag-implementation`, `conversation-memory`, `prompt-caching`, `llm-npc-dialogue`
Open-source registry and CLI for Claude Code components: agents, commands, skills, hooks, MCPs, settings and mods
Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents",…
Send and receive cryptographically signed messages between AI agents using the Agent Messaging Protocol (AMP). Use when the user…
Search auto-generated codebase documentation for function signatures, API docs, class definitions, and code comments. Use when…
Query the code graph database to understand component relationships, dependencies, and change impact. Use when the user asks to…
Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to…
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.