From Local Agent Toolkit
Give the agent durable, local memory with engram — recall past decisions before answering, and persist new decisions, preferences and facts as they happen. Use when work spans sessions or the user says "remember".
How this skill is triggered — by the user, by Claude, or both
Slash command
/local-agent-toolkit:engram-memoryThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You have access to a local, private memory layer ([engram](https://github.com/jnMetaCode/engram)).
You have access to a local, private memory layer (engram). Treat it as your long-term memory: read it before you answer, write to it when something durable happens. Everything stays on the user's machine.
If the engram_recall / engram_remember MCP tools are available, use those.
Otherwise use the CLI (zero install):
npx @jnmetacode/engram serve & # HTTP API on :7077, or
npx @jnmetacode/engram mcp # as an MCP server
Before answering anything that may depend on prior context, search memory first:
npx @jnmetacode/engram recall "pricing decision" --since month
Quote the recalled passage with its citation (file/date) rather than paraphrasing from your own context — the citation is the point.
Persist a memory when the conversation produces something with a shelf life:
npx @jnmetacode/engram remember "2026-06-10: chose scoped npm names (@org/pkg) because unscoped were taken"
Rules for good memories:
When a recalled memory turned out to be the correct answer — the fix worked, the user confirmed — say so, and similar future queries will rank that source higher:
npx @jnmetacode/engram reinforce "staging deploy fails" deploy-notes
(MCP: the engram_reinforce tool, {query, source}.) Only reinforce
verified answers; reinforcing guesses trains the memory to be confidently
wrong. For the full improvement loop, see the self-evolve skill.
After remembering, do a quick recall of a keyword from the new memory. If it
doesn't come back first, rewrite it more concretely.
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