query-memory
Searches through all project memory sources like KIs, ADRs, and domain dictionaries to provide comprehensive answers.
Install
mkdir -p .claude/skills/query-memory && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/19045" && unzip -o skill.zip -d .claude/skills/query-memory && rm skill.zipInstalls to .claude/skills/query-memory
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Registry-aware search across every memory source in shared/memory-registry.json — KIs and ADRs (by delegating to search-ki), plus the feature archive, DOMAIN_DICTIONARY.md, and TEAM_TOPOLOGY.md, which search-ki doesn't cover. Lexical only for now (the registry marks LightRAG disabled); verifies any future non-lexical result against canonical markdown before trusting it.Key capabilities
- →Search across knowledge items and architecture decision records by delegating to search-ki.
- →Search the feature archive for relevant content.
- →Check DOMAIN_DICTIONARY.md for query matches.
- →Search TEAM_TOPOLOGY.md for ownership and crossing questions.
- →Combine and rank results from multiple memory sources.
- →Verify non-lexical results against source markdown before presentation.
How it works
The skill loads `shared/memory-registry.json` to identify memory sources, delegates KI/ADR search to `search-ki`, and directly searches other sources like `feature-archive`, `domain-dictionary`, and `team-topology`.
Inputs & outputs
When to use query-memory
- →Searching project documentation
- →Finding architecture decisions
- →Querying domain dictionaries
- →Gathering collective team knowledge
About this skill
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
shared/memory-registry.json— which sources exist and their retrieval backend- 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.mdanddocs/features/*/analysis.mdfor relevant content — same judgment-based readingsearch-kiapplies, 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.
When not to use it
- →When the question is specifically about KIs/ADRs, use `search-ki` directly.
- →When promoting a single retrospective's decision, use `promote-memory`.
- →When auditing the corpus for duplicates, use `memory-engineer`.
Limitations
- →Search is lexical only, as `lightrag` is disabled in the registry.
- →Results are capped at 5 total across all sources.
- →Non-lexical backend results require markdown verification before presentation.
How it compares
This skill provides a unified search across diverse memory sources, unlike manually searching individual files or using `search-ki` which focuses only on KIs/ADRs.
Compared to similar skills
query-memory side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| query-memory (this skill) | 0 | 18d | No flags | Beginner |
| citation-management | 23 | 7mo | Review | Beginner |
| microsoft-docs | 10 | 4mo | Review | Beginner |
| peer-review | 11 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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