query-memory

Imported from orieken/saturday-monorepo (.claude/skills/query-memory/SKILL.md). Install upstream with npx skills add orieken/saturday-monorepo --skill query-memory. Copyright stays with the author.

When To Use

When a question could plausibly be answered by any memory source, not specifically KIs/ADRs — e.g. "what do we know about rate limiting" might be a KI, but might also be sitting in a past feature's retrospective, or be a DOMAIN_DICTIONARY.md term whose definition already answers the question.

Do NOT use when the question is specifically about KIs/ADRs — use search-ki directly, it's the more targeted tool and this skill calls into it anyway for that portion. Do NOT use for a single retrospective's promotion decision — use promote-memory. Do NOT use to audit the corpus for duplicates — use memory-engineer.

Context To Load First

1. shared/memory-registry.json — which sources exist and their retrieval backend
2. Per-source files, only after step 1 tells you which ones are relevant to the query (see Process)

Process

1. Read the Registry First

Load shared/memory-registry.json. This tells you which sources exist and whether any use a backend other than lexical — currently none do (lightrag is "status": "disabled"), so every search in practice is a markdown read, but check the registry rather than hardcoding that assumption, since it's meant to change without this skill needing a rewrite.

2. Delegate the KI/ADR Portion

Invoke search-ki for the knowledge-items and adrs registry sources — don't reimplement its pre-filter and judgment-based ranking here, that would be exactly the duplicated-logic problem memory-engineer exists to catch elsewhere.

3. Search the Remaining Sources Directly

For feature-archive, domain-dictionary, and team-topology (the sources search-ki doesn't cover):

• feature-archive: grep docs/features/*/retrospective.md and docs/features/*/analysis.md for relevant content — same judgment-based reading search-ki applies, not a keyword-only match.
• domain-dictionary: check if the query matches a defined term directly — if so, that's usually the most authoritative answer available.
• team-topology: only relevant for ownership/crossing questions, not general knowledge queries.

4. If a Non-Lexical Backend Is Ever Active

Per the registry's lightrag entry: any result retrieved through it MUST be verified against the source markdown file before being presented as fact — never surface a LightRAG result standalone. This step is inert today (nothing uses that backend yet) but is not optional once something does.

5. Rank and Cap

Combine results from all sources, rank by actual relevance to the question (not by which source it came from), and cap at 5 total — same discipline as search-ki's own cap, for the same reason.

Output Format

## Memory Query: "[query]"

### Matches
- [Result title] ([source: KI | ADR | Feature Archive | Domain Dictionary]) -- [one-line why it matches] -- [file link]

### No Match
[If nothing matches: "No memory source covers this — consider `create-ki` or `promote-memory` after this
task if the answer turns out to be reusable."]

Guardrails

• Never duplicate search-ki's KI/ADR logic — delegate to it.
• Never fabricate a match — say "no match" plainly, same as search-ki.
• Never present a non-lexical-backend result without markdown verification, if/when that backend is ever active.
• Cap at 5 results total across all sources combined, not 5 per source.

Standalone Mode

Pure local file reads plus a delegated call to search-ki (also pure local reads). No external calls, no embeddings, today. If lightrag is ever enabled per the registry, this skill degrades gracefully back to lexical-only if that backend is unavailable — markdown is always the fallback, never the other way around.

Part of the ai-assistant-dot-files Context Engineering Framework by Oscar Rieken — licensed under CC BY 4.0. If you copy or adapt this file, please keep this attribution.