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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。

Interact with Langfuse and access its documentation. Use when needing to (1) query or modify Langfuse data programmatically via the CLI — traces, prompts, datasets, scores, sessions, and any other API resource, (2) look up Langfuse documentation, concepts, integration guides, or SDK usage, or (3) understand how any Langfuse feature works. This skill covers CLI-based API access (via npx) and multiple documentation retrieval methods.

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。

Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.

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。

Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositories, domain events), facilitating Event Storming sessions, creating bounded context maps, or performing code reviews with a DDD lens. Covers both strategic design (bounded contexts, subdomains, context maps, ubiquitous language) and tactical design (entities, value objects, aggregates, domain services, repositories). Supports all major architecture patterns (Hexagonal/Ports & Adapters, CQRS, Event Sourcing, Clean Architecture) with language-agnostic guidance and concrete examples in Python and TypeScript.

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 the user wants to learn a topic or verify real understanding — rapid-competence session, error drills, learning sprint, gap probe, Feynman check. Triggers 'teach me X', 'quiz 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。

Use when polling external AIs (OpenAI, Anthropic) outside the host session for a neutral second opinion on a roadmap, diff, prompt, or file set — or 'cross-check with another model'.

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。

Periodically inspect a sprint manager and worker sessions against a sprint spec, classify progress, nudge only for real stalls, and always append a checkpoint log beside the sprint file.

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。

Join Claude Desktop or Codex Desktop to the Interlateral mesh as a desktop peer with its own tmux inbox session, identity, direct ACK, and ledger mirror. This is separate from the standard CLI init flow.

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。

Join the Antigravity CLI (agy, Gemini 3.5 Flash) to the Interlateral mesh as a native CLI peer with its own tmux session, identity stamping, and the agy.js send helper. Use this instead of the Antigravity desktop-app CDP path.

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。

[User-Invoked] Use ONLY when the user explicitly types /dual-ai or /dual-ai <workflow-id> — fans out one prompt, or one workflow invocation per tool, to two fresh parallel AI sessions (Claude Code + Codex CLI), both pre-set to xhigh reasoning effort and full-permission mode before the prompt executes. NEVER auto-activate.

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。

Mid-run failure recovery for disease-market-sizing-orchestration. Inspects .cache/<slug>/ to determine which phase last completed and which phase to run next. Use when orchestration was interrupted and user wants to continue without restarting from phase 1.

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 auditing or fixing prose that reads like a leaked reasoning transcript — dead design-session citations such as (decision N), audit item codes, or §N of uncommitted drafts; change narration such as "used to", "no longer", "this cut"; stack or review vantage ("a later PR in this stack", "rejected in review"); reviewer-addressed justifications; control-flow narration; or hedged planning residue in comments, JSDoc, docs, or Agent Notes.

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。

VRIO resource analysis combined with Dynamic Capabilities assessment. Use this skill to identify real competitive advantages (Barney VRIO framework), then test whether the organisation can sense new opportunities, seize them, and transform itself to stay ahead (Teece dynamic capabilities). Runs in three modes — full diagnostic for deep first-use sessions, review mode for quick re-assessment, and alert triggers for defining early-warning signals. Updates company-context.md after every run. Triggers on questions about competitive advantage, defensibility, resource assessment, why competitors are gaining ground, organisational agility, or whether advantages will hold. Based on practice by Eterdis (eterdis.com).

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。

Explicit retrospective of a coding session with evidence-backed suggestions for future 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。

Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession"...

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。

Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.

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。

Complete SolanaOS agent skill — install, configure, and operate the autonomous Solana trading runtime with Honcho v3 epistemological memory, multi-venue perp trading (Hyperliquid + Aster), on-chain intelligence with USD pricing, Telegram bot, gateway API, Tailscale mesh, hardware integration, and cross-session recall. Use when asked to install SolanaOS, query Solana blockchain data, manage wallets, run OODA trading loops, configure strategies, control BitAxe mining fleets, pair Seeker devices, or operate any SolanaOS runtime surface.

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。

Comprehensive Cline SDK skill for building AI agents. Covers the direct Agent runtime, ClineCore sessions, custom tools, plugins, events, LLM providers, scheduling, multi-agent teams, and production deployment. Use for any task involving @cline/sdk or its sub-packages.

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。

Verify a tested web agent's real behavior from its recorded Pi or Codex session and selected screenshots before scoring. The judge prompt provides absolute artifact paths; use targeted queries to compare actual outputs, errors, and the final answer with the recorded behavior, then return only the verdict JSON. Only for ego-bench judging—never to drive a browser or rerun the agent.

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。

Analyze code for primitive obsession and plan value object extractions around domain concepts, validation, and grouped primitive fields. Use when the user says `/value-objects`, asks for value object refactoring, or runs `/refactor:value-objects`.

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。

Refine an existing skill in place with minimal diffs. Trigger when asked to improve a skill's trigger description/frontmatter, workflow text, metadata, scripts/references/assets; also for requests to iterate, refactor, rename, or fix a skill using usage/session-mining evidence (for example from /tw-seq).

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。

Plan a cyclist's training week as a standalone coaching package with integrated workout building. Use whenever the athlete asks to plan a week or the upcoming week ("plan my week", "build my training week", "week schema", "plan a week workout schedule", or any localized equivalent), or states a goal for the week. The flow reads a per-athlete config, pulls recent Strava data, classifies rider type from the athlete's own power curve, then produces one weekly markdown plan and structured bike workouts (ZWO for Zwift) per structured bike session without relying on another skill. Works for any cyclist, not one fixed person.

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。

Load for Blazor BFF server work involving YARP proxy routes, cookie sessions, access-token forwarding/refresh, downstream API calls, BFF handlers, or browser-to-API auth failures; not for client component rendering or API JWT validation alone.

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。

Knowledge base from DOE Systems Engineering Methodology (SEM) Version 3 — the DOE SDLC for IT investments. Use for staged systems lifecycle planning through maintenance, Stage Exits, Structured Walkthroughs, In-Stage Assessments, requirements traceability, and CMM-aligned process discipline. Covers SEM3 (2002) guidance only; does not replace modern DevSecOps tooling standards, DOE O 413.3B capital-asset directives, or current CIO policy supersessions.

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。