procedural-memory
Give your AI agent a memory of how it solves tasks.
procedural-memory saves successful tasks as reusable skills. When a similar request comes in, it replays the saved steps instead of asking the LLM to solve the same problem again.
Solve it once. Reuse it next time.
USER REQUEST
│
intent + parameters ← one cheap classification call
│
┌────┴─────┐
│ STORE │
└────┬─────┘
┌──┴──┐
MATCH NO MATCH
│ │
SKILL AGENT → success check → compile → STORE
│ │
└────┬─────┘
RESULT
How it works
- Your agent receives a request.
- The library checks whether a matching skill already exists.
- If a skill matches, it replays the saved tool calls.
- If no skill matches, your agent solves the task.
- If the task succeeds, the library saves it as a reusable skill.
Features
- Save reasoning costs — reuse previous solutions instead of solving the same task again.
- Works with any LLM — you provide your own
classifyandcall_toolfunctions. - No dependencies — only Python 3.10+ is required.
- Sync and async — supports both synchronous and asynchronous functions.
- Safe by design — skills contain JSON tool calls, not executable code.
- Human-readable skills — inspect and edit saved procedures manually.
- Keep control — your existing permissions, confirmations, rate limits and auditing still apply.
Skills are learned only from successful executions. A skill is not saved if it depends on a fixed identifier or contains unused request parameters.
Install
pip install scriptflow-procedural-memory
Documentation
See SPEC.md for the skill format and technical details.
License
MIT
Metadata
Release files for scriptflow-procedural-memory 0.3.0
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