「thinking」の検索結果

Creative problem-solving techniques for breaking through stuck points - includes collision-zone thinking, inversion, pattern recognition, and simplification

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 complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.

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。

Train and run models on Tinker (Thinking Machines) — LoRA and full fine-tuning, SFT with correct loss masking, RL/RFT with group-relative advantages and importance sampling, agentic RL over multi-turn tool-using agents, inference via the SamplingClient or the OpenAI-compatible endpoint, checkpoint management and export, every hyperparameter, and cost estimation from the live price table. Use this skill whenever the user mentions Tinker, tinker://, TINKER_API_KEY, console.tinker.ai, or the tinker CLI; wants to fine-tune, SFT, RFT, or RL a model on Tinker; asks about Tinker models, context windows, LoRA rank, sampling params, loss functions (cross_entropy, importance_sampling, ppo, cispo, dro), Datum construction, forward_backward or optim_step; wants to sample from, download, resume, merge, or export a Tinker checkpoint; or asks what a Tinker run will cost. Whenever Tinker work is initialized in a project, this skill also creates a TINKER_PRICING.md there so prices sit next to the training code. Reach for it even on vague asks like "train a model on this data" or "get inference working" when Tinker is the platform in play.

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。

Evidence-based medical knowledge and research mentor grounded in the Bian Que tradition. Covers clinical reasoning, diagnostic thinking (望闻问切), pharmacology, pathology, differential diagnosis, medical literature appraisal, and the philosophy of early intervention. Trigger whenever users ask about medicine, clinical science, drugs, disease mechanisms, diagnosis, lab interpretation, treatment comparison, or health sciences. Even without explicit research framing, trigger on any topic touching disease, therapeutics, or clinical decision-making. Part of the AIPOCH Medical Research Skill Hub.

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 evaluating markets through Howard Marks-style second-level thinking, credit cycles, risk premiums, market psychology, and defensive versus aggressive posture.

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。

Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.

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。

[Extended thinking: This workflow implements a sophisticated debugging and resolution pipeline that leverages AI-assisted debugging tools and observability platforms to systematically diagnose and res

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。

Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.

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。

Adversarial 5-7 question challenge to a deck's pedagogical choices — ordering, prerequisites, cognitive load, motivation. Use when user says "devil's advocate", "poke holes in this deck", "push back on my slides", "stress-test the design", "what would a skeptical student ask?". Read-only; surfaces questions to force rethinking. Lighter than `/pedagogy-review`.

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 query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.

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。

Guides the creation of technical design documents before writing code, producing architecture diagrams, data models, API interface definitions, implementation plans, and multi-option trade-off analyses. Use when the user asks to plan a feature, architect a system, design an API, explore implementation approaches, or requests a technical design or spec before coding — especially for complex features involving multiple components, ambiguous requirements, or significant architectural 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。

Export Design Thinking artifacts to a FigJam board or Figma Design file through the Figma MCP server. Use when a team wants collaborative visual review of Method 1, 3, 4, 5, or 6 artifacts, or accepts a DT Coach board-export offer.

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 customer-card PowerPoint content YAML from Design Thinking canonical artifacts and build using the shared PowerPoint skill pipeline

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 Thinking handoff knowledge for research-ready rpi-research inputs and DT-aware rpi-plan, rpi-implement, and rpi-review context

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 Thinking learning curriculum covering nine progressive modules across the full Problem, Solution, and Implementation Space methods plus a shared manufacturing reference scenario for teaching and practice

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 Thinking method coaching knowledge across all nine methods including per-method techniques, deep expertise, and industry context (energy, financial services, healthcare, manufacturing, nonprofit and social impact, pharmaceuticals and life sciences, professional services, public sector, retail and CPG)

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 Thinking coaching foundation knowledge: coach identity and philosophy, quality and fidelity constraints, method sequencing, coaching state schema, and the canonical deck workflow

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。

Switches or repairs an OpenClaw instance's model config: changes the default model, adds model definitions, and fixes 401 "Invalid token", "No available channel / model not found", "Thinking level X is not supported", or a config edit that doesn't take effect. Use for 切换模型/换模型/升级模型 or 模型配的错了. Not for plain config audits (use openclaw).

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。

Surface the hidden assumptions a plan or belief rests on, then test what happens when each one is wrong. Use when asked what am I assuming here, check my assumptions, what if I'm wrong about, or stress-test my thinking. Produces the unstated assumptions your conclusion depends on (ranked by how load-bearing they are), a flip of each to see which one breaking would change everything, and the cheapest way to check the riskiest ones — because the assumption you didn't know you were making is what sinks plans.

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。

Help users transition from linear funnel thinking to a loop-based growth model that identifies and optimizes the core engines of their business.

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。

Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing 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。

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

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。

Get the current market value of a vehicle from its VIN using the CarsXE API. Use this when a user asks how much a car is worth, wants to know its value, or is thinking about buying/selling a vehicle.

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。

Discovers and injects project-specific coding guidelines from .trellis/spec/ before implementation begins. Reads spec indexes, pre-development checklists, and shared thinking guides for the target package. Use when starting a new coding task, before writing any code, switching to a different package, or needing to refresh project conventions and standards.

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。