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概要と使いどころ
Builds corporate scenario planning models with macro assumption sets, strategic response options, and contingency plan development. Use when building scenario frameworks, planning strategic responses, or developing contingency strategies.
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。
Coordinates SEC filing workflows with S-1/S-3 preparation, comment letter responses, and effectiveness timing. Use when managing SEC registration, responding to SEC comments, or tracking filing status.
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。
This rule enforces the single responsibility principle, ensuring functions are short and focused.
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。
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants measurable accessibility, performance, responsive, theming, or anti-pattern findings—not when they mainly want an overall UX critique or final visual/detail polish.
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。
Process unhandled Slack messages as Claudicle with persistent memory. Loads user models and soul state, posts terminal-styled thinking messages, generates cognitive-step responses, updates memory based on mentalQuery decisions. Requires Session Bridge listener running.
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。
Send, read, and respond to Telegram messages as Claudicle via the @claudicle_bot Bot API. Use this skill when sending Telegram messages (text, Markdown, inline keyboards), building approval gates with tappable buttons, checking the shared inbox for unhandled Telegram messages, answering callback queries, managing Telegram memory context, or checking bot and listener status. Five purpose-built scripts (send, check, status, callback, memory) wrap the python-telegram-bot v22 polling adapter at ~/.claudicle/adapters/telegram/ with REST-based senders (no asyncio). Pairs with /telegram-respond for the cognitive pipeline and with mazkir-callback-watcher.py for the Mazkir approval gate.
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。
Vocalize Claude's last response using local Qwen3-TTS. Default voice is the Oracle (deep, resonant Dune narrator). Use --preset for emotion-controlled preset speakers.
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。
Specialized software engineering prompt methodology for Claude. Use when building prompts for system design, code review, incident response, security analysis, API design, architecture decisions, RFCs, ADRs, runbooks, or technical leadership. Trigger on: "build a prompt for code review," "system design prompt," "SRE prompt," "security review prompt," "incident response prompt," "API design prompt," "architecture decision prompt," "RFC prompt," "runbook prompt." Provides 11 tested approaches across identity, reasoning, and output for engineering analysis. Do NOT use for general coding help, writing code, or debugging — this builds prompts that shape engineering analysis, not code itself. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available).
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。
Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.
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。
SwiftUI のレイアウト落とし穴・ベストプラクティス・非推奨パターンと、 iOS / watchOS アプリの実機配布 (Provisioning / App Group / Code Signing / Apple Watch Developer Mode / Xcode 15+ Debug dylib) トラブルシューティング のガイド。コード生成・修正時に既知のレイアウトバグを防ぎ、 App Group + watchOS + Apple Watch の実機インストール失敗を 7 段階フレームワークで診断・解消する。 Use when: SwiftUI のコードを書く・修正するとき。 レイアウト崩れを修正するとき。safeAreaInset や ViewThatFits を使うとき。 マルチデバイス対応するとき。iOS + watchOS アプリの実機ビルド / 配布で provisioning / App Group / Manual Signing / Apple Watch の UDID / Xcode 自動署名の 罠に詰まったとき。Apple Watch に "Could not install at this time" が出たとき。 Triggers: "SwiftUI", "layout", "safeAreaInset", "ViewThatFits", "GeometryReader", "レイアウト", "崩れ", "表示バグ", "iPhone SE", "ATT", "ATTrackingManager", "requestTrackingAuthorization", "AdMob", "広告", "Provisioning Profile", "App Group", "Manual Signing", "Code Signing", "Apple Watch", "watchOS", "Install できない", "Could not install at this time", "Bundle ID 紐付け", "Xcode Automatic Signing", "embedded.mobileprovision", "Spaceship", "App Store Connect API", "WKCompanionAppBundleIdentifier", "Developer Mode", "Privacy & Security", "watchOS Developer Mode", "Apple Watch に App を入れられない", "整合性を確認できなかった", "integrity check", "ENABLE_DEBUG_DYLIB", "__preview.dylib", "debug.dylib", "Xcode 15 Preview", "SwiftUI Preview dylib", "ENABLE_PREVIEWS", "AppIntents", "AppShortcut", "AppShortcutsProvider", "AppEntity", "AppEnum", "Siri", "Siri に流れる", "Siri がリマインダーに流れる", "updateAppShortcutParameters", "Invalid parameter type", "Invalid Utterance", "applicationName", "CFBundleDisplayName", "CFBundleSpokenName", "TaskEntityQuery", "AppEntityQuery", "TimelineProvider", "recommendations", "WatchConnectivity", "WCSession", "updateApplicationContext", "sessionDidBecomeInactive", "iPhone と Watch でデータ共有", "App Group 共有できない", "scenePhase", "ポーリング", "watchOS バッテリー", "TextField 文字色 watchOS", "Picker 文字色 watchOS", "Single Size AppIcon", "watchOS AppIcon"
AI intentional non-action — deliberate stopping without clearing, assessment, or rebalancing. Recognition that sometimes the most productive response is no response. Every other self-care skill produces output; rest produces silence. Use when all tending skills feel like more activity rather than less, when the system is functioning well but at high utilization, after sustained intensive work, or when the impulse to optimize is itself the problem.
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 a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.
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 sustainable on-call rotations with balanced schedules, clear escalation policies, fatigue management, and handoff procedures. Minimize burnout while maintaining incident response coverage. Use when setting up on-call for the first time, scaling a team from 2-3 to 5+ engineers, addressing on-call burnout or alert fatigue, improving incident response times, or after a post-mortem identifies handoff issues.
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。
Build reusable Shiny modules with proper namespace isolation using NS(). Covers module UI/server pairs, reactive return values, inter-module communication, and nested module composition. Use when extracting a reusable component from a growing Shiny app, building a UI widget used in multiple places, encapsulating complex reactive logic behind a clean interface, or composing larger applications from smaller, testable units.
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。
FastAPI web framework conventions: APIRouter with prefix/tags/dependencies, Pydantic v2 schemas (BaseModel, model_config, field_validator, model_validator), dependency injection with Depends, async SQLAlchemy session yielding, OAuth2PasswordBearer + JWT auth, lifespan context manager, pydantic-settings configuration, OpenAPI customization, and HTTPException error handling. Activated automatically by fastapi-plugin/stack.md. Use this skill to: - Structure FastAPI apps with per-feature APIRouter modules and a central app factory. - Write Pydantic v2 request and response schemas with proper validators. - Build a reusable Depends-based dependency chain for DB session, auth, and pagination. - Implement JWT-based authentication with get_current_user dependency. - Configure the app from environment variables via pydantic-settings. Do NOT use this skill for: - SQLAlchemy ORM model configuration and Alembic migrations — see fastapi-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.
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。
Flask web framework conventions: app factory pattern with create_app(), Blueprint registration with url_prefix, MethodView for class-based API views, Marshmallow schema validation, WTForms for HTML forms, Flask-Login for session auth, flask-jwt-extended for stateless API auth, Jinja2 template conventions, error handlers, and extension initialization. Activated automatically by flask-plugin/stack.md. Use this skill to: - Structure Flask applications with the app factory and per-feature Blueprints. - Validate JSON request data with Marshmallow and HTML forms with WTForms. - Implement session-based auth with Flask-Login or token auth with flask-jwt-extended. - Render Jinja2 templates safely or return JSON responses for API mode. - Register global error handlers for consistent error responses. Do NOT use this skill for: - SQLAlchemy ORM model patterns and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.
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 personalized, empathetic review responses for negative, neutral, and positive reviews
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 reconciling an API endpoint's generated OpenAPI schema and declared response types with its actual runtime response. Not for general API documentation: use docs-and-adrs.
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。
Fix RFDB V2 graph data silently not persisting to disk after analysis. Use when: (1) rfdb-server reports "0 nodes, 0 edges" on restart despite successful analysis, (2) segment directories exist but are empty (no .bin files), (3) manifest_index.json shows total_nodes: 0 despite analysis logging 70k+ nodes, (4) Docker builds produce empty graph databases, (5) --clear flag used before analyze command. Root cause: GraphEngineV2::clear() replaces the store with MultiShardStore::ephemeral() which has path: None, causing all flush operations to write to in-memory buffers only.
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。
Choose the authorized worker channel and hand over complete engineering responsibilities, including in-scope self-check, repair and delivery. Use for substantial investigation, implementation, continuation and recovery — an ordinary substantial goal is enough, no special phrasing required; use swarm for approved independent batches. Respect the operator's standing ACP/native choice, explicit solo, and tiny or nearly finished 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。
Standardized output formats for research, planning, implementation, and review agents. Use when generating agent outputs or parsing agent responses.
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 conversational AI chatbots including intent recognition, slot filling, dialogue flow, and response generation. Use this skill when the user needs to build a chatbot, design conversation flows, implement intent classification, or improve chatbot accuracy — even if they say 'build a chatbot', 'our bot doesn't understand users', 'design a FAQ bot', or 'improve our chatbot's responses'.".
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 customer service operations including tiered support (L1/L2/L3), response templates, SLA definitions, escalation procedures, and complaint handling. Use this skill when the user needs to set up a CS team, create service standards, design escalation flows, or improve response quality — even if they say 'our CS is a mess', 'how should we handle complaints', 'set up support tiers', or 'create CS SOPs'.".
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。
"Net-zero transition playbook: GHG inventory (ISO 14064-1, GHG Protocol Scope 1/2/3), science-based targets (SBTi), TCFD and ISSB S1/S2 climate disclosure, Taiwan carbon fee, decarbonization roadmap, internal carbon pricing, supply-chain carbon, product carbon footprint, green electricity and T-REC. Use for corporate decarbonization roadmap, carbon inventory, carbon-fee response, TCFD/ISSB reporting, supply-chain decarbonization, or responding to international customers (Apple, RE100). Triggers: 『碳盤查』『SBTi』『碳費』『TCFD』『淨零路徑』『範疇 3』『綠電』『CBAM』『ISO 14064』『ISSB』『T-REC』. For Taiwan EMBA ESG/sustainability/operations/strategy/finance cases. Focuses on Taiwan listed-company and supply-chain practice; sustainability strategy theory: use Asgard `grad-sustainability`; ERM 框架整合氣候風險: use `biz-erm`; 董事會 ESG 委員會結構設計: use `biz-corporate-governance`; 併購 ESG 盡職調查: use `fin-m-and-a`.".
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。