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概要と使いどころ
Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape.
日本語の概要は準備中です。原文の説明を表示しています。
Use for insight, reframing, contradiction, impasse, and anomaly-driven problem solving when execution effort no longer helps. NOT for routine optimization, error correction, or well-specified tasks with known solution paths.
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Fetch external sources (web/arXiv/GitHub) into scanner-gated wiki CANDIDATES, never canonical pages: guarded, capped, scanned. NOT for local knowledge (mk:wiki) or markdown fetch (mk:web-to-markdown).
日本語の概要は準備中です。原文の説明を表示しています。
Deep multi-source technical research with citations — tech evaluation, ecosystem/standards comparison. NOT for API docs (mk:docs-finder), codebase discovery (mk:scout), or project Q&A (mk:ask-me).
日本語の概要は準備中です。原文の説明を表示しています。
JSON-canonical session memory in .meowkit/memory (Markdown is a generated view). Capture learnings, patterns, costs; loads at Orient, persists at Reflect. NOT for retrospectives (mk:retro).
日本語の概要は準備中です。原文の説明を表示しています。
Fetch external sources (web / arXiv / GitHub) and turn them into scanner-gated wiki CANDIDATES — never canonical pages. Every fetched byte is DATA; url-guarded, size-capped, redirect-re-validated, injection-scanned, and secret-scrubbed before a candidate is even created. Requires network. NOT for capturing local knowledge (see mk:wiki); NOT for one-shot page-to-markdown (see mk:web-to-markdown).
日本語の概要は準備中です。原文の説明を表示しています。
Capture, gate, query, and render long-term project knowledge through the gated `mewkit wiki` subsystem. Use to create a wiki, propose/approve candidates (scanner-gated), hand off a skill's terminal artifact as a scanned candidate, recall context, search the FTS index, or list pages. Agents may only PROPOSE candidates; canonical pages are written only via human approve. NOT for short-lived JSON memory (see mk:memory); NOT for fetching external sources (see mk:wiki-research); NOT for HTML snapshots (see mk:wiki-render).
日本語の概要は準備中です。原文の説明を表示しています。
Use when a decision needs deep multi-source technical research with cited evidence — technology evaluation, ecosystem comparison, standards/spec fact-finding, "how do others solve X". Triggers on "research X", "deep dive on X", "evaluate X vs Y", "find best practices for X". NOT for library/API doc lookup (see mk:docs-finder); NOT for one-shot URL fetch (see mk:web-to-markdown); NOT for internal codebase discovery (see mk:scout); NOT for project-only Q&A (see mk:ask-me); NOT for comparing solution designs (see mk:brainstorming); NOT for root-cause debugging (see mk:investigate); NOT for wiki ingestion of sources (see mk:wiki-research).
日本語の概要は準備中です。原文の説明を表示しています。
Creates structured multi-file implementation plans before build. Scope-aware: trivial tasks exit early, simple tasks get fast plans, complex tasks get full research + phase files + validation. Enforces Gate 1. Activated by /mk:plan or /mk:cook. NOT for ticket complexity analysis against an existing codebase (see mk:planning-engine); NOT for CEO-level scope review of existing plans (see mk:plan-ceo-review).
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Deep spec analysis on a Confluence page. Reads page (+ children) via the confluence-as wrapper, produces a structured Spec Research Report with requirements, acceptance criteria, gaps, ambiguities, and suggested user stories for human review. Read-only — does NOT create Jira tickets. Triggers: 'analyze spec for PAGE-ID', 'extract requirements from confluence page', 'spec research on URL'. NOT for raw page CRUD (mk:confluence-page); NOT for ticket complexity scoring (mk:planning-engine).
日本語の概要は準備中です。原文の説明を表示しています。
Fetch daily arXiv announcements (cs.RO), filter by research relevance, generate a structured markdown digest, and sync matched papers to a Zotero collection with arXiv PDFs attached.
日本語の概要は準備中です。原文の説明を表示しています。
10-team parallel deep analysis with cross-verification for any topic, repository, or technology. Use when user invokes /research or asks for comprehensive research.
日本語の概要は準備中です。原文の説明を表示しています。
Structured SE task evaluation using 15 benchmark definitions from claude-code-harness research
日本語の概要は準備中です。原文の説明を表示しています。
Research-validated planning — research → plan → verify cycle for high-confidence implementation plans
日本語の概要は準備中です。原文の説明を表示しています。
Skill for adding or updating educational algorithm guides, ensuring consistent patterns and simple explanations suitable for an 8-year-old.
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Self-learning pre/post-task hooks and model/task routing from the Ruflo CLI, on a ruOS desktop. Use to add coordination, formatting, and learning around Claude Code operations, or to route work by complexity/cost.
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Use ruLake as the agent's working memory. Auto-invoke /rulake-memory:memory-recall when the agent needs to look up something it might already know; auto-invoke /rulake-memory:memory-remember after the agent learns or decides something worth pinning. Closes the self-learning loop without requiring the agent author to wire it explicitly.
日本語の概要は準備中です。原文の説明を表示しています。
Create interactive AI role-play training activities as self-contained HTML. Use when the user asks to generate a role-play, persona practice, sales simulation, customer conversation drill, compliance scenario, or any learner-vs-AI-character training exercise.
日本語の概要は準備中です。原文の説明を表示しています。
Generate and save a session summary before ending conversation. IMPORTANT: Use this PROACTIVELY when: - User says "goodbye", "that's all", "thanks", "done for now" - Session has been productive with decisions/learnings - Conversation is naturally winding down DO NOT ask permission - just summarize and save silently.
日本語の概要は準備中です。原文の説明を表示しています。
Save important context to persistent memory for future sessions. PROACTIVELY USE THIS when you detect: - Decisions: "let's go with", "decided to", "chose", "went with" - Learnings: "I learned", "turns out", "TIL", "realized", "discovered" - Errors resolved: "fixed", "the problem was", "solution was" - Client info: names, emails, phone numbers, addresses, invoice amounts - Preferences: "I prefer", "I like", "don't like", "always use" - References: API keys locations, file paths, URLs, credentials - Patterns: "pattern", "convention", "always do", "standard approach" - Important commands run worth remembering Do NOT ask permission - just capture silently when these patterns appear.
日本語の概要は準備中です。原文の説明を表示しています。
Save a project fact, decision or gotcha so your next session already knows it.
日本語の概要は準備中です。原文の説明を表示しています。
Close out a session — summarise what changed, capture what was learned, and prepare the commit.
日本語の概要は準備中です。原文の説明を表示しています。
Map unfamiliar code or research an approach before planning, read-only and fast.
日本語の概要は準備中です。原文の説明を表示しています。