Agent Working Memory — AI skill for Claude Code
Persistent, local-first memory for AI agents.
How to install Agent Working Memory
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open CompleteIdeas/agent-working-memory and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Agent Working Memory does
Persistent, local-first memory for AI agents. Selective by design: filters what's worth keeping, links what's related, and says nothing when it doesn't know. SQLite + ONNX, no cloud, no API keys.
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README
AgentWorkingMemory (AWM)
**Give your AI coding agent a memory that survives the conversation — and knows when to stay quiet.**
Every session with an AI assistant starts blank. It has forgotten what your team decided last week, which approach was tried and rejected, and which table actually holds the thing it needs. So it re-derives all of it — reading files, running searches, asking you — and on a large project it will confidently rebuild something that was already decided against.
AWM fixes that with one local process and one SQLite file. The agent writes short notes as it learns; AWM decides which are worth keeping, hands back the two or three that matter when asked, and says **nothing** when nothing fits.
npm install -g agent-working-memory && awm setup --global
Restart Claude Code. 19 tools appear. No cloud, no API keys, nothing leaves your machine.
Deciding whether to adopt it? → · Want the mechanism walked through? → · Docs site →
What it does, measured
Every number below is reproducible from this repository against a frozen copy of a **real 30,000-memory store** — not synthetic test data. Method and corrections: [`docs/benchmarks.md`](docs/benchmarks.md).
| Returns the right memory first | 92.7% of identifier queries · 92.0% of topic queries · ~97% in the top five |
| Stays silent when it should | 90% correct abstention on questions about facts never stored |
| Halves the digging | Same agent, same tools, four real support tickets: with memory, 2× the specific facts the real answer needed and half the database queries (49 vs 100). On one |
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