basic-memory

Sleep-time memory reflection: review recent conversations and daily notes, extract insights, and consolidate into long-term memory. Use when triggered by cron, heartbeat, or explicit request to reflect on recent activity. Runs as background processing to improve memory quality over time.

Research an external subject using web search, synthesize findings into a structured Basic Memory entity. Use when asked to research a company, person, technology, or topic — or when a bare name or URL is provided that implies a research request.

Schema lifecycle management for Basic Memory: discover unschemaed notes, infer schemas, create and edit schema definitions, validate notes, and detect drift. Use when working with structured note types (Task, Person, Meeting, etc.) to maintain consistency across the knowledge graph.

Task management via Basic Memory schemas: create, track, and resume structured tasks that survive context compaction. Uses BM's schema system for uniform notes queryable through the knowledge graph.

Use when explicitly creating or updating a Basic Memory pull request. This compatibility entry point delegates the full workflow to pull-request and the latest-head Codex gate to pr-review-loop.

Use when opening or updating a GitHub PR - writes a detailed PR description that explains what changed, why it changed, how it was implemented, and how it was tested.

Enforce the Basic Machines GitHub PR review loop before merging. Use whenever Codex is preparing to merge, squash-merge, auto-merge, declare a PR ready, monitor Codex comments, address review feedback, or wait for Codex approval on a GitHub PR, especially when the user says "approved", "merge", "ship", "PR is ready", "monitor Codex comments", or "address Codex feedback".

Drive GitHub pull request work end to end. Use when Codex is asked to open, update, describe, push to, monitor, review, address comments on, declare ready, or merge a PR. Covers branch hygiene, PR descriptions with why/what/testing/risk, CI checks, Codex review-loop monitoring, comment handling, and the final merge gate.

Write, refactor, and review Python for clarity, explicit behavior, local reasoning, strong types, constructive domain modeling, and minimal abstraction. Use when creating or changing nontrivial Python, simplifying object-heavy, helper-heavy, or overly procedural code, evaluating whether code is Pythonic, or reviewing Python maintainability in Basic Memory repositories.