Save facts, decisions, and discoveries to agentmemory for future sessions. The skill preserves the user's wording, adds specific search tags and referenced file paths, and confirms which terms can retrieve the saved knowledge.
Save an insight, decision, or learning to agentmemory's long-term storage with searchable concept tags. Use when the user says "remember this", "save this", "note that", "don't forget", or wants to preserve knowledge for future sessions.
Review the instructions the agent will receive before you install.
The user wants to save this to long-term memory: $ARGUMENTS
memory_save {
"content": "We rotate JWT refresh tokens on every use; the old token is revoked server-side in auth/refresh.ts.",
"concepts": "jwt-refresh-rotation, token-revocation, auth-flow",
"files": "src/auth/refresh.ts"
}
Expected output:
Saved memory abc12345 with 3 concepts: jwt-refresh-rotation, token-revocation, auth-flow.
A memory is only as useful as the terms that retrieve it. Tag with specific
concepts so a future recall finds it, and preserve the user's own phrasing.
$ARGUMENTS.jwt-refresh-rotation beats auth).memory_save with content, concepts (comma-separated string), and
files (comma-separated string). In a multi-agent setup pass agentId so
the memory lands in the right agent's scope.WRONG: concepts: "stuff, code, notes" (generic tags nothing can find later).
RIGHT: concepts: "jwt-refresh-rotation, token-revocation" (specific, retrievable).
recall: retrieve what you save here (the pair to this skill).forget: remove a memory you saved by mistake.lesson: behavioral rules from corrections; memories are for facts.memory-discipline: when to save unprompted.See TROUBLESHOOTING.md if memory_save is not available.
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Connect agentmemory to coding agents such as Claude Code and Codex while preserving existing server settings. It guides configuration, host restarts, and checks that memory tools are available and can save and retrieve information.
Explain how agentmemory stores and retrieves coding agents’ memories, including its engine, search methods, memory lifecycle, ports, and web viewer. Useful for understanding the system or planning extensions to its functions.
Set up and troubleshoot a local agentmemory server by checking MCP connections, authentication, ports, and environment settings. Understand which optional memory features require additional configuration, model downloads, or token usage before enabling them.
Understand how agentmemory automatically records tool activity, prompts, and session boundaries through hooks, actions triggered by session events. Use it to check integration setup, investigate missing records, and distinguish capture from optional summaries and context injection.
Helps agents choose the right agentmemory tool through MCP, a protocol for connecting agents to tools. It explains tool roles and points to parameter references for saving, retrieving, organizing, and maintaining stored knowledge.
Guides HTTP integration with the agentmemory server for saving and searching knowledge. It explains authentication, request conventions, and endpoint references, including how to connect systems that do not support MCP, the agent tool connection protocol.