Memory

Skill ngocsangyem/MeowKit/.claude/skills/memory

Production ready. AI Agent Workflow System for Claude Code

Install

npx -y skills add ngocsangyem/MeowKit --skill memory

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

15 stars15 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

JSON-canonical session memory. Use when capturing session learnings, extracting patterns, or tracking costs — persists to .meowkit/memory JSON stores; matching Markdown files are generated views. Activates during Phase 0 (Orient) to load context and Phase 6 (Reflect) to persist it. NOT for weekly-cadence engineering retrospectives (see mk:retro); NOT for arbitrary file storage.

SKILL.md

4.1 KB, as published. Nobody here has run it

Memory System Toolkit

Reference guides for the memory system: session capture, pattern extraction, and cost tracking.

When to Use

During Phase 0 (Orient) to load previous session context
During Phase 6 (Reflect) to capture learnings and patterns
When the analyst agent tracks costs or extracts patterns

Workflow Integration

Operates in Phase 0 (Orient) and Phase 6 (Reflect). Output supports the analyst agent.

References

Reference	When to load	Content
capture-architecture.md	Before any agent-side memory write	The 2-path contract — `##prefix:` is user-typed only; agents write via direct `Edit`
session-capture.md	Phase 6	Capturing session learnings in 3 categories (patterns/decisions/failures)
pattern-extraction.md	Phase 6	Extracting high-frequency patterns for instruction-file promotion
cost-tracking.md	Phase 0, 6	Token usage tracking, cost reporting, budget alerts
consolidation.md	Manual	Prune stale entries, merge duplicates, archive cost data (run when memory grows large)

How session-capture is invoked

session-capture is not a CLI subcommand. At Phase 6 (Reflect) the agent reads references/session-capture.md and follows its 4 steps using Read / Write / Edit directly. There is no mewkit memory session-capture script — content extraction requires LLM analysis that a static CLI cannot produce.

Subcommands

`--prune`

Prune old standard-severity entries from canonical JSON stores, then regenerate Markdown views.

Stores subject to pruning: fixes.json, review-patterns.json, and architecture-decisions.json.

What gets pruned:

## headings with a date (YYYY-MM-DD, severity: standard) older than threshold (default: 90 days)

What is exempt:

severity: critical or severity: security entries — never pruned
Entries without a parseable date — kept as-is (safe default)

How to run:

/mk:memory --prune              # default 90-day threshold
/mk:memory --prune --days 180   # custom threshold
/mk:memory --prune --dry-run    # show what would be archived without moving

Mechanism: prune schema entries in JSON by lastSeen and severity, then run mewkit memory render-views. Report the affected stores and entries.

Recovery: Copy entries from lessons-archive.md back to the appropriate topic file.

Schema Notes

Split JSON files (fixes.json, review-patterns.json, architecture-decisions.json) all use v2.0.0 schema with fields: version, scope, consumer, patterns[], metadata. Each pattern entry supports: id, type, category, severity, domain, applicable_when, context, pattern, frequency, lastSeen.

Gotchas

Stale patterns applied to changed codebase: Memory suggests patterns from old architecture → Run consolidation when patterns exceed 50 entries; flag patterns with lastSeen > 6 months
cost-log.json growing unbounded: Every session appends without pruning → Run consolidation to archive entries older than 90 days
Generated views are not writable: Do not write lessons.md or Markdown topic files. Update the canonical JSON store, then render views.