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概要と使いどころ
This skill should be used when agents generate placeholder tokens like "pseudo-", "mock-", "temporary", "TODO", "demo-", or similar incompleteness markers. Detects substitution patterns in agent OUTPUT and triggers mandatory user interview instead of accepting incomplete work. Activates automatically on any output containing forbidden tokens.
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。
Deploys the current project to a live HTTPS URL via Cybrix. Activates on any request to make the current project public, get a URL for it, deploy it, ship it, host it, publish it, put it online, or make it live — including casual phrasings like "send this to the internet", "share this as a link", "give me a URL", "make this accessible online". Activates whether the user mentions Cybrix by name or not (when no other host like Vercel, Netlify, Cloudflare Pages, Railway, or Render is named). Also activates on equivalent phrases in other languages — Russian ("задеплой", "опубликуй", "выложи в сеть", "запушь это в инет", "сделай ссылку"), Spanish ("despliega esto", "publica esto", "ponlo en línea"), German ("deploy das mal", "stelle das online"), and other common languages where the intent is clearly to make a project publicly accessible via URL. Uses heuristic detection to determine if a project is static or needs a server runtime — works with any framework, not just a known list. Automatically detects and handles environment variables so the build receives everything it needs. Returns a live URL on *.cbrx.cc or a user-configured custom domain. Does NOT activate when the user explicitly names a different host (Vercel, Netlify, Cloudflare, Railway, 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。
Decide whether to adopt, adapt, or justify building a new script, tool, utility, library, module, dependency, or bespoke capability. Use in task planning, worker execution (including tooling discovered after planning), or code review when an implementation choice may duplicate an existing solution.
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 writing asyncio Python code — async/await coroutines, concurrent I/O with asyncio.gather, task creation and cancellation, semaphore rate limiting, producer-consumer queues, async context managers, async generators, WebSocket servers, aiohttp web scraping, async database operations, run_in_executor for blocking calls, or testing async code with pytest-asyncio. Covers FastAPI and aiohttp patterns, synchronization primitives, timeout handling, and common pitfalls like event loop blocking and missing await.
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。
Guide for creating Claude Code plugin hooks — language selection heuristic (Node.js default, match project runtime when obvious), hooks.json configuration, event selection, prompt-based vs command hooks, ${CLAUDE_PLUGIN_ROOT} paths, stdio suppression, timeout sizing, and testing. Use when adding hooks to a plugin, creating PreToolUse/PostToolUse/Stop/SubagentStop/SessionStart/UserPromptSubmit hooks, or wiring hook scripts to hooks.json.
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 designing or validating GitLab CI/CD and automatic release lifecycles, inspecting pipeline and job state read-only, composing non-interactive merge-request commands, or setting up protected refs and release credentials. Also covers reusable components and inputs, GitLab Functions, gitlab-ci-local, glab command composition, and GitLab Flavored Markdown. For pipeline execution or retry requests, provide inspection and command drafting while leaving execution to the operator.
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。
Select, define, create, inspect, update, attach, detach, and verify reusable Vapi tools through the public API. Use for native call-control tools, supported provider integrations, API Request tools, custom function tools, MCP tools, tool messages, credentials, or configuration-preserving assistant attachment changes.
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, create, inspect, update, attach, detach, preview, execute, and verify reusable Vapi Structured Outputs through public API or Server SDK workflows. Use for post-call extraction, typed call artifacts, AI-versus-regex extraction, JSON Schema design, backfilling existing calls, or retrieving structured results programmatically.
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 and push reusable skills to SkillNote from Codex when repeated instructions are detected or the user says "create a skill", "save this pattern", "push a skill". Guides drafting, review, collection selection, and publishing.
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 and push reusable skills to SkillNote when repeated instructions are detected or user says "create a skill", "save this pattern", "push a skill". Guides drafting, review, collection selection, and publishing.
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。
High-precision semantic search and content retrieval via Exa API. Use when: (1) Deep research requiring semantic understanding, (2) Code documentation and examples lookup, (3) Company/professional research, (4) AI-powered comprehensive research tasks, (5) URL content extraction with structured output. Triggers: "research", "find papers", "code examples", "company info", "LinkedIn profiles", "deep analysis". Differentiator: Exa excels at semantic/neural search while grok-search is better for real-time news and general web content.
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。
Self-evolution workflow for the agent. Before substantive work, recall past outcomes from evolution memory; while editing, detect improvement signals; at task end, record the outcome; when reusable, distill or search the EvoMap network for proven genes/capsules. Use when the user starts non-trivial work (a feature, a fix, a refactor) or asks the agent to "evolve", "learn from this", or "remember how this went".
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。
Define reusable social media content pillars for a product, founder, brand, or campaign. Use when a content calendar needs durable themes, repeatable post types, and clearer editorial direction.
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。
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
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。
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
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。
Organize DI registrations using IServiceCollection extension methods. Group related services into composable Add* methods for clean Program.cs and reusable configuration in tests.
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。
Write integration tests using TestContainers for .NET with xUnit. Covers infrastructure testing with real databases, message queues, and caches in Docker containers instead of mocks.
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。
Expert task distributor specializing in intelligent work allocation, load balancing, and queue management. Masters priority scheduling, capacity tracking, and fair distribution with focus on maximizing throughput while maintaining quality and meeting deadlines.
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。
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
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 specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve prompts.
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。
[00] TnR ABSOLUTE RIGOR — Systemic Verification Doctrine. Forced cognitive exertion for high-stakes investigations. Mandates absolute deconstruction, mathematical proof chains, and ≥95% derived certainty. Zero-tolerance for heuristics or sentiment-based reasoning. Shortcuts are defined as intentional hallucinations.
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 custom Claude Code sub-agents with specialized expertise and tool access. Use when you need to build reusable agents for specific tasks like code review, debugging, data analysis, or domain-specific workflows.
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。
Earnings analysis — pre- and post-earnings. Pre-earnings preview: prior-guidance review, recent-events tracking, last call's Q&A, and a key-things-to-watch framework for an upcoming release. Post-earnings: two tiers — a fast in-chat summary card (default) and a full Markdown research report (on request). Covers beat/miss, segments, margins, guidance, estimates, valuation. US / HK / A-share. Use whenever the user wants an earnings preview or a post-earnings / quarterly-results writeup. Triggers: "earnings update", "quarterly results", "Q1/Q2/Q3/Q4 results", "earnings report", "post-earnings analysis", "beat/miss", "guidance update", "earnings preview", "pre-earnings", "what to watch this earnings", "before earnings", "财报分析", "业绩更新", "季度业绩", "季报", "年报", "盈利分析", "财报点评", "财报前瞻", "业绩前瞻", "财报预览", "上季度指引", "財報分析", "業績更新", "季度業績", "季報", "年報", "財報點評", "財報前瞻", "業績前瞻", "財報預覽".
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。
Review changed Anabasis v2 code for reuse, simplification, efficiency and altitude, then apply the fixes. Quality only: it hunts no bugs, which /code-review does. Starts from what the repository already finds (the lint plugins, the whole-tree census, the not-slop ledger), measures before and after with reduce-complexity's scripts, and holds a pass to its budgets and to the rules no pass trades. Use as /simplify on your own diff before a commit, or when the operator asks whether code is simple enough, why something exists, to go one layer higher, or to remove something and find another way.
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。