「rd」の検索結果

C-suite orchestrator — routes to advisor roles, triggers board meetings, cross-functional

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 a complete TypeSpec API plugin for Microsoft 365 Copilot that calls external REST APIs, with operations, authentication, and Adaptive Card responses. Use when building a Microsoft 365 Copilot API plugin with TypeSpec.

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。

Add GET, POST, PATCH, and DELETE operations to a TypeSpec API plugin with proper routing, parameters, and adaptive cards. Use when extending an existing Microsoft 365 Copilot TypeSpec API plugin with new REST operations.

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。

Cascades strategy from boardroom to individual contributor. Detects and fixes misalignment between company goals and team execution. Covers strategy articulation, cascade mapping, orphan goal detection, silo identification, communication gap analysis, and realignment protocols. Use when teams are pulling in different directions, OKRs don't connect, departments optimize locally at company expense, or when user mentions alignment, strategy cascade, silo, conflicting OKRs, or strategy communication.

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。

Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity.

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 and maintain one coherent company story across all audiences — employees, investors, customers, candidates, and partners. Detects narrative contradictions and ensures the same truth is framed for each audience's needs. Use when preparing investor updates, all-hands presentations, board communications, recruiting narratives, crisis communications, or when user mentions company narrative, messaging consistency, storytelling, all-hands, investor update, or crisis communication.

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。

Product leadership for scaling companies. Product vision, portfolio strategy, product-market fit, and product org design. Use when setting product vision, managing a product portfolio, measuring PMF, designing product teams, prioritizing at the portfolio level, reporting to the board on product, or when user mentions CPO, product strategy, product-market fit, product organization, portfolio prioritization, or roadmap strategy.

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。

Builds AI-powered trading and financial analysis agents with multi-agent LLM architectures: research pipelines, sentiment signals, portfolio optimization, backtesting, risk guardrails, and market monitoring. Use when designing or implementing an LLM-based trading or market-analysis system.

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 a complete AGENTS.md at the repository root following the agents.md format: setup, build, test, style, and PR conventions coding agents need. Use when a repo has no AGENTS.md, when onboarding coding agents to a codebase, or when the existing agent instructions are stale.

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 skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.

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 skill should be used when the user asks to "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration.

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 asks to work on a Python FastAPI project. Triggers on keywords Python, FastAPI, Pydantic, SQLAlchemy.

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。

Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo

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。

Runs an autonomous experiment loop on any programming task: you define the goal, metric, and eval command; the agent edits code, measures, and keeps or discards each change until interrupted. Use when optimizing a measurable target (speed, accuracy, size, score) by iteration.

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。

Triggers on keywords RAG, GraphRAG, vector database, agentic RAG, semantic search

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。

Integrate a GPU operator into ATREX with minimal source, compatible lazy APIs, hardware dispatch, atrex-prefixed kernels, one functional test file, and target-GPU 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。

Refactor Swift code toward declarative functional programming with immutability, value types, pure functions, transformations, and closure-based APIs. Use when asked for functional refactoring or `/refactor:functional`.

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。

Refactor a class toward the Single Responsibility Principle by identifying responsibilities, grouping cohesive behavior, and extracting focused classes. Use when the user says `/srp`, asks for SRP refactoring, or runs `/refactor:srp`.

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 the latest learning as a numbered markdown file under ~/.claude/learnings and update the learnings index with title and tags. Use when the user says "save", asks to record a learning, or wants the current insight stored for later.

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 implementing a new function, adding a feature, fixing a bug, refactoring with test coverage, or writing a new test. Enforces strict outside-in red-green-refactor TDD with one-failure-per-turn discipline, predict-the-failure-before-every-run checks, hardcode-first minimum changes, triangulation, and property-based testing for large input spaces. Triggers on explicit TDD requests and on any task phrased as "implement", "add", "write a function", "build a feature", or "fix a bug" in a test-capable codebase. Reports red/green validation evidence.

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。

Systematically explore an unfamiliar codebase and build a reusable architecture summary. Use for repo onboarding, understanding legacy or inherited code, mapping architecture before a migration or refactor, tracing a bug or feature path, or answering "what does this project do?". Documentation-first, then data flow — ends in a concise technical architecture summary with file:line evidence, not a raw file dump.

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 one explicit escalation pass using the original glaze prompt words verbatim. Use when prompts say `/tw-glaze`, when the first answer feels merely adequate, or when you want the exact original rhetoric preserved while pushing for a materially stronger 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。

Post-launch review of a shipped PRD against the brief's success metrics. Did we move the metric? What did the data actually show? Which assumptions held, which broke? Which accepted-gap decisions resolved (confirmed vs. invalidated)? What would we do differently? Triggers on "outcome review", "did it work", "post-launch review", "did we move the metric", "retro the feature", "was it worth it". Produces a Confluence outcome-review page and updates the brief + linked decisions.

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+fix protocol with optional pre-core git diff review and safety guardrails (unsoundness, invariants, footguns, incidental complexity). Use when prompts say "/tw-fix this PR", "fix current branch", "fix this diff", "repair CI red", or "apply a minimal patch", and when crash/corruption/invariant-break issues need correction with a validation signal. Stop only after self-review exhausts actionable changes, each full cycle reaches post-self-review rerun plus terminal diff-review closure, and two consecutive zero-edit full cycles are clean.

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。