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code-review

Use when reviewing Basic Machines code for house style, architecture risk, pre-merge hardening, or whether a change fits basic-memory/basic-memory-cloud conventions.

Quellinformationen

Repository
basicmachines-co/basic-memory
Letzte Quellaktivität
9. Juni 2026 um 20:18
Erkannte Sprache von SKILL.md
Englisch
Sterne
4.494
Forks
350

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
code-review
description
Use when reviewing Basic Machines code for house style, architecture risk, pre-merge hardening, or whether a change fits basic-memory/basic-memory-cloud conventions.
license
MIT
# Basic Machines Review Use this skill for repo-local review passes where ordinary code review needs Basic Machines house style and architecture judgment. Report findings only; do not edit code unless the user asks you to fix specific findings. ## Scope Review the current diff or named files against: - The repo's `AGENTS.md` / `CLAUDE.md` - `docs/ENGINEERING_STYLE.md` - The touched code paths and tests Apply only the guidance for the active repo. In `basic-memory`, prioritize local-first file/database/MCP boundaries. In `basic-memory-cloud`, prioritize tenant/workspace isolation, cloud worker behavior, and web-v2 state/runtime boundaries. ## Review Rubric Report only concrete, falsifiable risks: - **Cognitive load:** Is the change harder to understand than the problem requires? - **Change propagation:** Will one product change force edits across unrelated layers? - **Knowledge duplication:** Is the same rule encoded in multiple places that can drift? - **Accidental complexity:** Did the change add abstractions, fallbacks, or state without need? - **Dependency direction:** Are API/MCP/CLI, services, repositories, and UI stores respecting their intended boundaries? - **Domain model distortion:** Do names and types still match the product concept, or did a transport/storage detail leak into the domain? - **Test oracle quality:** Would the tests fail for the bug or regression the change claims to protect against? ## House Rules To Check Explicitly - No speculative `getattr(obj, "attr", default)` for unknown model shapes. - No broad exception swallowing, warning-only failure paths, or hidden fallback behavior. - No casts or `Any` that hide an unclear type relationship. - Dataclasses for internal value/result objects; Pydantic at validation/serialization boundaries. - Narrow `Protocol`s when only a capability is needed. - Explicit async/resource ownership, cancellation, and cleanup. - Meaningful regression tests or verification for risky changes. - Comments explain why, not what. ## Reporting Format Lead with findings ordered by severity. Each finding should include: | Severity | Use for | | -------- | ------- | | `high` | A likely correctness, security, data-loss, or tenant/workspace isolation failure | | `medium` | A concrete maintainability or boundary risk that can cause future defects | | `low` | A minor consistency issue, ambiguous guidance, or review-only cleanup | ```text severity | file:line | risk category | claim Why: concrete behavior or code path that proves the risk. Fix: smallest practical change, or "none obvious" if the risk needs product input. ``` If there are no findings, say so and note any verification gaps that remain.
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