memory-query-capture

name	memory-query-capture
description	Capture query synthesis as durable pages in semantic memory
namespace	aiwg
category	kernel
platforms	["claude","copilot","cursor","factory","windsurf","warp","codex","opencode","openclaw","hermes"]

memory-query-capture

Capture valuable assistant synthesis from conversation into durable semantic memory pages. This is the compounding primitive — explorations accumulate as reusable knowledge rather than evaporating into chat history.

When to Use

Any time an assistant response produces analytical output worth preserving: comparisons, gap analyses, architectural assessments, synthesis narratives. Invoked explicitly by the user, suggested ambiently by the system, or chained automatically by other skills.

Parameters

--consumer (optional)

Consumer ID to write against. Resolved via ADR-021 D4 precedence: explicit > wrapper > auto-detect.

--type (optional)

Page type: synthesis, comparison, analysis, or gap. If omitted, determined by heuristic or user prompt.

--title (optional)

Page title. If omitted, derived from content via headline extraction or summarization.

Invocation Modes

Ambient mode

Suggested automatically when a query response exceeds a length/value threshold. The system presents a capture prompt; the user confirms or dismisses.

Explicit mode

User invokes directly: "save this as a page", "capture that comparison", or calls memory-query-capture with parameters.

Skill-chain mode

Any skill can call memory-query-capture as a final step after producing analytical output. The calling skill passes --type and --title to skip heuristics.

Operation

1. Capture synthesis — extract the last assistant synthesis from conversation state.
2. Determine page type — from --type flag, content heuristic, or user prompt.
3. Resolve consumer — determine target consumer via ADR-021 D4 precedence (explicit > wrapper > auto-detect).
4. Resolve destination — read memory.topology.derivedPages from consumer's manifest.json and select the matching subdirectory (derivedPages.synthesis, derivedPages.comparison, etc.).
5. Title the page — from --title flag or derived from content (first heading, key noun phrase, or summarized label).
6. Add cross-references — identify source pages cited in the synthesis and insert cross-reference links per the consumer's crossRefStyle setting.
7. Write page — create the Markdown file at the resolved destination path.
8. Update index and log — call memory-log-append with --op query-capture and metadata about the captured page.
9. Mark provenance (optional) — record query origin, model actor, and sources cited in a provenance block at the end of the page.

Page-Type Heuristics

When --type is not provided, the skill inspects the synthesis content:

Content pattern	Assigned type
Comparison table, side-by-side columns	comparison
Narrative prose with connective reasoning	synthesis
Gap analysis, missing coverage, "what's absent"	gap
Bullet-point assessment, evaluation criteria	analysis

If the heuristic is ambiguous, prompt the user to select.

Consumer Resolution

Follows ADR-021 D4 precedence:

1. Explicit — --consumer flag provided on invocation.
2. Wrapper — a parent skill passes consumer context down the chain.
3. Auto-detect — inspect .aiwg/frameworks/registry.json for the active consumer with a memory.topology contract.

If no consumer can be resolved, abort with a clear error requesting --consumer.

Cross-Reference Style

The consumer's manifest.json declares a crossRefStyle — one of:

• wikilink — [[page-name]]
• markdown — [page name](relative/path.md)
• at-mention — @consumer/path/to/page.md

The skill reads this setting and formats all source-page links accordingly.

Error Handling

• If no synthesis content is available in conversation state, report "nothing to capture" and exit.
• If the destination directory does not exist, create it before writing.
• Log write failures via memory-log-append are non-blocking — the page write is the primary operation.
• If consumer topology lacks a derivedPages mapping for the resolved type, fall back to the consumer's base memory directory.

Schema Reference

@semantic-memory/schemas/memory-log-event.md

Examples

# Explicit capture after a deep comparison
memory-query-capture --consumer research-complete --type comparison --title "Redis vs Valkey feature matrix"

# Ambient capture (system-suggested, user confirms)
> Your comparison of caching strategies looks worth preserving. Capture as a page? [Y/n]
memory-query-capture --type synthesis

# Skill-chain: architecture-evolution calls capture after producing assessment
memory-query-capture --consumer sdlc-complete --type analysis --title "Microservices migration readiness"

Storage Routing (#934, #966)

This skill's persistence flows through resolveStorage('memory'). On the default fs backend the memory subsystem lives at .aiwg/memory/ and behavior is byte-identical to direct file writes. To redirect memory artifacts into Obsidian, Logseq, Fortemi, or another backend without changing this skill, configure .aiwg/storage.config (#934).

Fortemi storage routing here is only a persistence backend choice. It does not switch semantic-memory query capture to the Fortemi Core index/search backend; memory records join that preview through the artifact export/sync path and are queried with explicit --backend fortemi-core graph commands.

When this skill needs to read or write memory artifacts from a Bash step:

aiwg memory path                        # resolved root (fs only)
aiwg memory list --prefix research-complete/
aiwg memory get research-complete/index.md
echo "# index" | aiwg memory put research-complete/index.md
echo '{"op":"ingest","summary":"foo"}' | aiwg memory append-log research-complete/.log.jsonl

The aiwg memory append-log subcommand uses atomic O_APPEND (#976) on the fs backend — concurrent appenders don't race.