Results for “thinking”

Thinking frameworks for decisions and problem analysis. Use when evaluating options, root causes, or prioritizing.

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Triggers for automatically invoking the decision-framework skill before irreversible or high-blast-radius operations. Use as a checkpoint: when a proposed action matches a trigger pattern, pause and run the appropriate framework (first-principles, inversion, decision matrix, second-order thinking) before proceeding. Prevents ad-hoc calls from becoming regret.

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Linear algebra and higher-dimensional thinking. Vectors, matrices, transformations — the architecture of mathematical space.

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ACSets (Attributed C-Sets) for categorical database design and DPO rewriting

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用户在帖子没爆时感到焦虑、怀疑自己是否适合做 X,或连发一批内容后评估整体表现、设定增长目标时使用。核心认知:公共平台传播是长尾分布(3861 帖均值 188/中位数 42),一条没爆是预期的中位数而非失败;目标不是让每条都爆,而是系统性提高进前 10% 的概率。Trigger signals: "我连发20条只2条过百该放弃吗""怎么让每条都爆""发了这么多没水花""一条没爆就怀疑人生""是不是我不适合做X" / "only 2 out of 20 hit 100, should I quit" "how to make every post go viral" "my posts get no engagement"。不适用于:单条内容生产(用 x-short-content-craft)、数据复盘操作(用 x-data-review)、理解推荐算法机制(用 x-foryou-algorithm)。

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Use when facing unknowns, debugging without a clear cause, or making architecture decisions — enforces hypothesis-driven scientific reasoning through observation, hypothesis formulation, prediction, experiment design, and evidence-based conclusion. Use when previous attempts have failed or the problem space involves uncertainty.

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Same reverse-thinking method as dh:rt-ica (see dh:rt-ica or dh-glossary for the definition), but localizes any MISSING input to the affected task only, as a non-blocking information-completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Use dh:rt-ica instead at the S2 implementation gate where missing inputs must halt execution.

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Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

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Apply systematic problem-solving techniques for marketing challenges including campaign complexity (simplification cascades), creative blocks (collision-zone thinking), recurring campaign patterns (meta-pattern recognition), assumption constraints (inversion exercise), audience scale uncertainty (scale game), and dispatch when stuck. Techniques derived from proven problem-solving frameworks adapted for marketing execution.

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Use when reviewing, debugging, or giving feedback on Go code in this repo (exercises/part2, website/tools, or any *.go file) or when asked for a "code review", "review this Go", "revisa este código Go", or "crítica de código". Reviews for correctness, idiomatic Go, error handling, resource cleanup, concurrency, performance, and security, and always ends with a test-thinking pass (what a test would catch). For exercises/part2, prefer the go-exercise-reviewer skill which knows the module-mode quirk; this skill covers general Go anywhere in the repo.

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Search and read locally-stored Claude documentation covering Claude Code CLI, Claude API (Messages, tool use, vision, streaming, batch), Agent SDK (Python and TypeScript), prompt engineering, and all Anthropic platform docs. Use this skill whenever the user asks about Claude Code features (hooks, MCP servers, skills, plugins, settings, permissions, keybindings, sub-agents), the Anthropic API or any of its SDKs (Python, TypeScript, Go, Java), the Agent SDK (sessions, hooks, custom tools, MCP), model capabilities (context windows, extended thinking, pricing, rate limits, vision), prompt engineering best practices, or troubleshooting any Claude-related error. This skill provides instant access to official documentation files without web searches — always prefer it over web lookups for Claude and Anthropic topics.

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当用户在评估一只股票"便不便宜"、纠结该不该基于PE/PB做买卖决策、 或试图用DCF公式精算企业价值时，激活此skill。 核心判断信号：用户提到"估值""PE多少倍""DCF模型""算一算值多少钱"， 或在纠结"这个价格能不能买"。 此skill将估值从数学计算还原为商业判断——用"未来现金流折现"作为思维 方式而非公式，通过"毛估估"判断是否明显便宜，以"封仓十年"的视角检验 理解深度，用E/E替代PE以纳入负债影响。 不适用于：需要精确估值建模的场景（如并购定价）、短期交易择时、 无法产生现金流的资产（如加密货币）。

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Strategic analysis gate for existing products — multi-dimensional evaluation (tech, product, design, business) using Design Thinking + 9 Windows (TRIZ) + Double Diamond. Outputs 2-3 qualified options with recommendations. Use BEFORE cm-planning for complex initiatives and enhancements on existing codebases.

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Use to run the second-brain loop — turn captures in raw/ into clean, cross-linked knowledge in wiki/, and to answer questions from past thinking. Trigger on "/wiki", "process my raw notes", "update the wiki", "add this to my brain/wiki", "what did I think about X", "what do my notes say about X". Follows references/sops/wiki-translate.md. Enforces the admission policy: no PHI, no live financials, no secrets in the committed wiki.

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Use when the user brings an external source worth keeping — a URL, a paper, a tweet/thread, a blog post, a docs page — and wants it pulled into the second brain. Fetches the source into the git-ignored capture inbox, admits it to the committed wiki through the admission policy, then refreshes the knowledge graph so it joins the rest of your thinking. Trigger on "/graph-ingest", "ingest this url", "add this paper to my knowledge", "add this tweet/page to my knowledge", "capture this source".

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将复杂问题拆解为层次分明、不重叠不遗漏的结构框架。适用于需要梳理混乱信息、向他人清晰表达、全面分析问题的场景。当你面对一堆散乱的要素无法形成全局视图，或需要向他人做结构化汇报时使用此skill。不适用于已经高度结构化的问题或需要直觉判断的快速决策场景。关键触发信号："信息太多理不清"、"怎么说才清楚"、"有没有遗漏"、"帮我拆解这个问题"。

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从要素到关系、从局部到整体、从静态到动态地分析复杂系统。适用于问题反复出现、牵一发动全身、头痛医头无效的场景。当你发现"越努力越糟糕"或"问题总是复发"时，需要切换到系统性思维找根本解。不适用于简单的单因果问题或需要快速行动的紧急场景。关键触发信号："为什么这个问题反复出现"、"改了A反而坏了B"、"感觉陷入了死循环"。

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Test a half-formed idea in a questioning conversation, with different personas probing its weak points, until the user can act on it or drop it with confidence. Optionally writes a short brief for planning skills to build on. Use when the user says 'forge an idea', 'pressure-test this idea', 'stress-test my thinking', or 'harden this idea'

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Use when working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).

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当用户面临复杂决策、规划或问题解决时激活——尤其是正向推理陷入困境、选项过多无法判断优先级、或需要识别隐藏风险时。典型触发信号：用户在问"怎么才能成功""如何避免失败""我应该怎么做"时卡住了。不适用于已有明确最佳路径且只需执行的简单任务,也不适用于需要创意发散而非风险规避的场景。

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Conduct an adaptive interactive interview on any topic and produce a structured markdown report, summary, or implementation plan. Use when the user says "interview me", "interview me about", "run an interview on", "help me think through", or wants guided discovery on any subject. Also triggers on "talk me through", "explore X with me", "help me plan Y", or "walk me through my thinking on Z" when the user wants a guided conversation rather than a direct answer. Applies broadly — career decisions, project ideas, product direction, personal goals, research questions, team problems — not just technical topics.

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Construct well-structured arguments using the hypothesis-argument-example triad. Covers formulating falsifiable hypotheses, building logical arguments (deductive, inductive, analogical, evidential), providing concrete examples, and steelmanning counterarguments. Use when writing or reviewing PR descriptions that propose technical changes, justifying design decisions in ADRs, constructing substantive code review feedback, or building a research argument or technical proposal.

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Generate probability-weighted alternative options that challenge default thinking. Forces unconventional alternatives and exposes hidden assumptions behind the "obvious" choice. For decision-point analysis, NOT full design exploration. Triggers on "대안", "alternatives", "옵션 뽑아", "options", "어떤 방법이", "아이디어", "다른 방법", "선택지".

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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.

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