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Get Started Free →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".
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 119% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 150% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 95% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 200% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 287% | 0% |
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):
bashnpx @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:
in the current conversation.
bashnpx @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:
bashnpx @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:
bashnpx @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.
Other measured skills in the registry, with their headline benchmark lift.