vc:agent-browser

AI-optimized browser automation CLI with context-efficient snapshots. Use for long autonomous sessions, self-verifying workflows, video recording, and cloud browser testing (Browserbase).

mengram-memory

Long-term memory with 3 types (facts, events, workflows). Remember user preferences, past conversations, and learned procedures across sessions. Use when recalling what the user said before, saving important info, getting user context, or tracking completed workflows.

claude-memory

Access the persistent memory database (PostgreSQL `claude_memory`) for long-term context across Claude Code sessions. Triggers on "what do I know about", "memory lookup", "recall", "memory db", "what did we decide about", "similar conversations", "lookup context", "/memory". Provides semantic search, SQL queries and the ability to add new insights.

rlm

Run a Recursive Language Model-style loop for long-context tasks. Uses a persistent local Python REPL and an rlm-subcall subagent as the sub-LLM (llm_query).

ralph-wiggum-codex

Use when a coding task needs an objective-first long-running loop with fresh-context work and review phases, explicit acceptance criteria, resumable state, and real blocked handling.

gemini-delegate

Use when the task is dominated by large-context reading, synthesis, long-form drafting, bilingual or CJK writing, or second-opinion review rather than bulk code generation. Typical triggers include English or Chinese summaries of large source material, cross-file synthesis, terminology alignment, release-note drafting, and reviewer-style passes over documentation or generated output.

Optical Context MCP

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

ai-coding-workflow

Use when the user wants to work with Codex, Claude Code, or other AI coding agents more efficiently, especially to avoid long-session slowdown, split large tasks into bounded steps, define scope and non-goals, separate diagnosis from implementation, compress context between sessions, or turn a vague coding request into a tighter execution prompt. Also use when the user asks for an AI coding prompt/template, asks why AI coding gets slower later in a task, or wants a repeatable collaboration workflow for medium-to-large codebases.

Multi-vendor AI coding knowledge base. Auto-synced docs for Claude Code, Cursor, Codex, OpenAI, Gemini. Long-term context for AI agents — clone, open, ask.

headroom

Use when a Python or TypeScript app sends large tool outputs, logs, JSON, search results or long chat history to an LLM and the task is to cut input tokens, reduce token cost, fit a context window, or trim tool results without losing errors. Adds the headroom-ai compress() call; in-process, no API key, no model download.

chronicle-read

Reconstruct prior context (decisions, commitments, timelines) from /chronicle chapter summaries and timestamped paragraphs when long-term continuity matters

chat-compactor

Generate structured session summaries optimized for future AI agent consumption. Use when (1) ending a coding/debugging session, (2) user says "compact", "summarize session", "save context", or "wrap up", (3) context window is getting long and continuity matters, (4) before switching tasks or taking a break. Produces machine-readable handoff documents that let the next session start fluently without re-explaining.

supermemory

Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.

mem0

Integrate Mem0 Platform into AI applications for persistent memory, personalization, and semantic search. Use this skill when the user mentions "mem0", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python and TypeScript SDKs, framework integrations (LangChain, CrewAI, Vercel AI SDK, OpenAI Agents SDK, Pipecat), and the full Platform API. Use even when the user doesn't explicitly say "mem0" but describes needing conversation memory, user context retention, or knowledge retrieval across sessions.