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概要と使いどころ
Plan and execute cloud migrations to Azure from on-premises or other clouds. Use this skill when users ask for discovery, migration waves, cutover, validation, or modernization during migration.
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。
Safely localize unknown Unity games, especially Japanese-to-Chinese projects. Use to discover Unity version/layout/backend, migrate translations across game versions, extract occurrence-mapped text from serialized assets, embedded CSV, bytecode, UI, Localization StringTables, Utage, or middleware, bridge rows through AiNiee-style translation, validate and transactionally write approved candidates, audit residual and runtime-only text or AutoTranslator diffs, diagnose TMP fonts and Addressables/IL2CPP failures, locate saves, or acceptance-test SHA-verified patches.
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。
客户需求发现与澄清助手：当用户是销售、客户成功或售前，拿到客户模糊、宽泛、缺少产品边界的需求，需要先在内部最多五轮补齐关键事实，再生成一次性客户澄清问题清单、需求摘要与通用技术可行性判断时使用；当确认需求将落入 StyleWork 时加载可选产品与 UI 上下文，并可在信息足够或明确要求时输出带假设标记的轻量 Demo。不要用于直接报价、承诺交期、替代正式 PRD 或在信息不足时假装已有能力。
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。
Delegate implementation to Codex, grok, or cursor-agent, then review the diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants Codex, the grok 后端, or cursor-agent to write code, mentions handing off / delegating implementation to one of those backends, asks to work through a plan or spec unit-by-unit with an implementation backend doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer runs in the real environment behind backend-specific git and publication boundaries, must not be pointed at a full test suite by default, and its self-report is a claim rather than evidence. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the engineering-mode skill when it is installed.
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。
Delegate implementation work to a dedicated implementer subagent, then review its diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants a separate model to write code, mentions handing off / delegating implementation, asks to work through a plan or spec unit-by-unit with a subagent doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer self-reports success, must not run the full test suite by default, must not touch git, and its report is a claim rather than evidence. Cursor port of implementation-loop. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the cursor-engineering-mode skill (it ships in this same plugin).
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。
Trigger when: (1) the user mentions "manim", "scene", "video", "EN/KO render", "GEODE_HERO_LANG", "1080p60", or (2) editing files under `scripts/visualizations/` ending in `.py`, or (3) the user asks to render, re-render, or extend any of the four validated scenes (`geode_hero.py`, `autoresearch_filewalk.py`, `autoresearch_compare.py`, `critical_floor.py`). GEODE Manim Scene authoring standard. Locks the patterns the four validated scenes already share — Anthropic-style palette, Helvetica Neue + Pretendard font pairing with weight=NORMAL, EN/KO multilingual lang via `GEODE_HERO_LANG` env, `_dashed_arrow_with_head` stage-coupled tinting, `verify_hero_layout.py` ratchet — so the next scene does not re-discover the kerning / padding / transition regressions catalogued in [[viz-frame-audit]].
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。
Audit and improve Generative Engine Optimization as a measurable discovery-to-citation pipeline. Use for /geo, AI-search visibility, citation readiness, and GEO benchmark work.
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。
Trigger when: (1) the user mentions "noise", "slop", "frame audit", "video review", "letter spacing", "padding intrusion", "frame extract", "naive arrow", or Korean equivalents (노이즈, slop, 프레임 검수, 글자 깨짐), or (2) after rendering a new or modified Manim scene, or (3) the user asks to review an mp4 in `media/videos/` or `~/Downloads/`. Post-render audit workflow for Manim 1080p60 videos. Extracts keyframes via ffmpeg, inspects them through Claude Code's Read tool, and classifies any defects into four standing categories (naive arrow / padding intrusion / glyph kerning drift / frame-order error). Catalogues 12+ verified incidents across the four GEODE scenes so each is caught the first time, not rediscovered. The companion authoring skill is [[manim-scene-craft]].
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。
Discover and run tests that provide meaningful evidence for a code change. Use after implementation, before handoff or commit, or when the user asks to validate behavior.
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。
Manages Pi packages across their lifecycle: discovers, audits, installs, upgrades, removes, enables, disables, filters, and configures extensions, skills, prompts, and themes from npm, Git, or local sources. Use before any Pi package install or upgrade, when reviewing available updates, changing package activation or configuration, or maintaining the package inventory.
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。
Researches and compares free and open source software projects in a supplied domain, using either user-named candidates or a discovered shortlist. Use when evaluating FOSS alternatives, comparing GitHub popularity, maintenance, licences, domain fit, trade-offs, or producing a linked HTML comparison report.
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 durable project or workflow knowledge discovered during work. Use when a mistake, hidden constraint, repeated question, or changed behavior reveals a documentation gap. To root-cause one specific mistake the agent just made and let the user pick fixes, use `learn` (`/learn`) instead.
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。
Establish concise, cross-agent project instructions from repository evidence. Use when initializing or repairing AGENTS.md, CLAUDE.md, related discovery links, or project-specific agent guidance.
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。
Discover and run the linters and format checks relevant to changed code. Use after code edits or when the user asks for lint, formatting, or static-analysis validation.
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。
Generates California-compliant privilege logs for withheld or redacted discovery materials under CCP 2031.240. Use when the user mentions privilege log drafting, California privilege log, CCP 2031.240, attorney-client privilege logging, work product designation, Evid. Code 952/954, CCP 2018.030, redaction logging, meet-and-confer privilege disputes, waiver analysis, common interest doctrine, or asks for help documenting withheld documents. Also trigger on references to Hernandez v. Superior Court, Costco Wholesale, or Wellpoint.
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。
Produces an attorney-ready memo from a corpus of legal documents supplied by the user. Use when a user shows up with a folder, zip, or vault of case documents and asks for a case summary, case evaluation, litigation package, intake memo, matter overview, or "can you summarize this case for me." The skill ingests the corpus into a searchable index, OCRs anything non-searchable, inventories and diagnoses the practice area, loads the appropriate practice-area playbook module(s) (PI/tort, commercial litigation, IP infringement, or user-authored extensions), iteratively searches the corpus across eight core dimensions plus any module-specific dimensions, defers specialized document clusters (depositions, medical records, discovery, liens) to dedicated sibling skills, and synthesizes a cited memo.
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。
Transforms police body camera transcripts into structured 10-section legal summaries with timestamp-cited verbatim statements, constitutional issue spotting, evidence inventory, and probable cause articulation. Maintains strict neutrality for all parties. Use when analyzing BWC footage for discovery, pre-trial prep, or trial. Trigger: body camera, BWC, body worn camera, officer footage, use of force review, incident summary.
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。
Citation format and verification protocol for legal documents that draw on Bates-stamped source records. Defines the bracket citation format, multi-source citation rules, quotation handling, the verification pass that runs before output, and the [UNVERIFIED] flag protocol. Use this skill any time another skill produces a legal work product that cites Bates-stamped pages, including medical chronologies, deposition summaries, demand letters, case briefs, and discovery responses. Also use any time the user asks how to format a citation or verify that a claim is supported by the source.
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。
Validates and summarizes the four required authorization forms in a personal injury matter (retainer, HIPAA release, insurance authorization, employment record release). Confirms signatures, dates, scope, and completeness to determine readiness for the investigation phase. Use when reviewing client onboarding packets, verifying authorization forms before discovery, or checking HIPAA and record-release compliance.
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。
Drafts U.S. commercial real estate access and indemnity (right-of-entry) agreements for pre-closing due diligence. Covers license grants, non-invasive vs invasive testing gates, insurance/endorsement requirements, indemnity with discovery carve-outs, restoration and lien remedies, confidentiality, and anti-indemnity guardrails. Trigger: access agreement, right of entry, due diligence access, Phase I/II, invasive testing, pre-PSA site inspection.
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。
Generate llms.txt files from project docs per the llmstxt.org spec, for AI-friendly documentation indexes and discoverability. Use to create or update llms.txt for AI assistants.
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。
JIRA custom field discovery + configuration via jira-as. Create/configure-agile need admin. NOT setting per-issue field values (mk:jira-issue update).
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。
Design and safely evolve data models, schemas, migrations, queries, indexes, and ORM data-access boundaries. Discover the existing engine and migration source before proposing syntax.
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。