「signal」の検索結果

Bench instruments and measurement techniques for electronics — digital multimeter, oscilloscope, logic analyzer, spectrum analyzer, function generator, power supply, and their proper use. Covers probing technique, ground loops, loading effects, trigger modes, FFT mode pitfalls, signal integrity, noise budget analysis, and debugging workflows from "it doesn't work" to "here is the failure mechanism." Use when measuring, debugging, or characterizing any electronic circuit or firmware-hardware interaction.

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Climate physics, forcing, feedback, and attribution. Covers the greenhouse effect and radiative forcing, climate sensitivity, fast and slow feedbacks, the paleoclimate record, detection and attribution science, regional climate impacts, and the distinction between weather, climate variability, and forced climate change. Use when reasoning about global warming mechanisms, interpreting temperature or CO2 records, evaluating attribution claims for extreme events, or distinguishing signal from natural variability.

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The fifteen fundamental cooking techniques that together cover most home kitchen work. Organized by the transformation they perform (heat transfer, water management, emulsion, ferment, cut) rather than by cuisine. Covers knife work, sauté, sear, braise, roast, poach, boil, steam, grill, bake, stew, reduce, deglaze, emulsify, and pickle/ferment, each with the physics, the signal, the common failure, and a diagnostic question. Use when teaching a cook, substituting a technique, or diagnosing why a dish failed.

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Systems programming from memory management through networking. Covers memory models (stack vs heap, manual allocation, garbage collection, ownership/borrowing), concurrency (threads, mutexes, channels, async/await, actor model, data races vs race conditions), operating system concepts (processes, virtual memory, page tables, system calls, file descriptors, signals), compilation (lexing, parsing, code generation, linking, static vs dynamic libraries), networking fundamentals (TCP/IP, sockets, HTTP, DNS, TLS), and the hardware-software boundary (caches, cache lines, false sharing, memory-mapped I/O). Use when working with low-level code, diagnosing system-level bugs, understanding performance characteristics, or bridging between high-level languages and machine behavior.

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Recognition and mitigation of systematic reasoning errors documented in the heuristics and biases tradition. Covers confirmation bias, availability, anchoring, representativeness, framing effects, hindsight bias, overconfidence, and motivated reasoning. Each bias is presented with its mechanism, diagnostic signal, and structured mitigation. Use when you suspect your own or another reasoner's conclusions may be shaped by systematic cognitive distortion rather than evidence.

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Manages skill-creator integration with GSD workflows including skill loading, session observation, bounded learning guardrails, and pattern detection. Use this skill whenever: executing any GSD phase (to ensure relevant skills are loaded first), starting or resuming a work session (to check for pending suggestions), the user asks about skills, patterns, or skill-creator status, performing code changes that might represent repeating patterns, the user corrects Claude's output (highest-signal observation), or when skill refinement, creation, or suggestion review is discussed. Critical for maintaining the adaptive learning layer.

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Functions, categories, and information. How mathematical objects relate to each other — morphisms, entropy, signal processing.

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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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用户在周期性复盘 X 内容数据、分析哪些内容类型表现好、决定下步内容策略调整时使用。四步闭环:数据收集(拉曝光/互动/收藏)→原因分析(按内容类型对比,查Hook/Body/CTA)→优化迭代("如果重来怎么做更好")→记录追踪(Notion模板闭环)。找20%贡献80%价值的内容加倍投入。周复盘聚焦数据(互动率),月复盘审视战略(变现路径)。Trigger signals:"这周发了15条怎么复盘""哪些类型互动高""下周内容策略怎么调""帮我分析数据"/"weekly content review""which content type performs better""optimize next week's content"。不适用于:单条内容生产(用x-short-content-craft)、帖子没爆焦虑心态(用x-longtail-strategy)、理解推荐算法机制(用x-foryou-algorithm)。

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Unified messaging via Beeper Desktop MCP. Search chats, send messages, manage conversations across all networks (iMessage, WhatsApp, Signal, Telegram, Discord, Slack, etc.)

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Synthesis step in the multi-angle technical research pipeline. Receives structured outputs from all four research angles (api-state, ecosystem-research, impact-measurement, codebase-auditor), applies cross-angle signal weighting and conflict resolution, and produces a single synthesized Research section. Invoked by the technical-researcher orchestrator after all angle skills complete. Returns content to the orchestrator — does not write to the backlog.

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Where a dispatched step puts its output, and how it signals state upstream.

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Reviews Node.js runtime behavior in JavaScript or TypeScript, including server entrypoints, route handlers, middleware, streams, processes, dependencies, and environment configuration. Loads alongside language and CLI checks when applicable; investigates blocking I/O, backpressure, injection, lifecycle leaks, and misleading failure signals.

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Use for architecture review, dependency graphs, coupling analysis, or circular dependency detection. Establishes project module namespaces and traces imports plus Claude plugin hook, skill, script, PEP 723, and MCP boundaries. Emits partitioned Mermaid graphs with cycle, coupling, and ownership signals; verifies contract and consequence before assigning severity. Registers diagrams as codebase-analysis artifacts.

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Reviews CLI application code for correctness and quality. Use when reviewing tools that use argparse, click, typer, commander.js, or similar argument parsers — covers exit codes, help flags, stdin/stdout/stderr separation, non-interactive operation, signal handling, argument validation, ANSI color safety, and dry-run support for destructive operations.

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Look up prior Claude Code sessions when context is lost or forgotten. Use when asked what was done before, what happened in the last session, or any request to recall past conversation history, prior decisions, experiments, or outcomes. Indexes and searches raw JSONL transcripts from ~/.claude/projects/ via DuckDB. Returns verbatim user messages, summarizes AI actions and sub-agent outcomes, detects tool errors and user frustration signals, and reports tool usage statistics. Summaries cached at ~/.claude/kaizen/session-summaries/.

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Shapes for running many sub-agents at once — fan-out with a barrier, maker/checker, generate-and-filter, tournaments for ranking, hypothesis fan-out for root cause, and loops that stop on a condition with a cap. Use when a phase has several independent targets, when a task is too large or too repetitive for one window, when the same edit applies across many files, when ranking or judging a large set, when several hypotheses compete, or when work must repeat until a signal says stop. Does not apply when units depend on each other's results or the cause is still unknown — investigate first, then parallelize.

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Use for Deepline GTM work that searches, enriches, scores, collects signals, or automates a workflow: find companies or people, enrich a CSV, find emails or LinkedIn, compare providers, build a waterfall, create a webhook or cron, or write a Play. For live information work, run a small heterogeneous experiment, exploit the observed winner, and reopen misses. Skip pure copywriting and non-GTM research.

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Use when discovering niche signals, auditing ICP or won/lost evidence, rescoring accounts, or building account and lead scoring Plays. Triggers on fit scoring, engagement scoring, external proxies, and scoring leakage. Skip pure outreach copy or contributor skill installation tasks.

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Self-hosted skill registry for OpenClaw. Stores procedures your team writes (name, description, body), syncs them to disk before each task, and collects which-helped/which-failed signals from the agent so the registry improves over time.

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库无关的Flutter/Dart代码审查清单，涵盖Widget最佳实践、状态管理模式（BLoC、Riverpod、Provider、GetX、MobX、Signals）、Dart惯用法、性能、可访问性、安全性和整洁架构。

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Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.

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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".

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Technical analysis frameworks — candlestick patterns, Ichimoku cloud, technical indicators (RSI/MACD/EMA/Bollinger), harmonic patterns (Gartley/Bat/Butterfly/Crab), Elliott Wave, Chan Theory (缠论 bi/zhongshu/buy-sell points), Smart Money Concepts (BOS/FVG/Order Block), and Turtle Trading signals with ATR/Unit position sizing. Triggers: "技术分析", "K线形态", "蜡烛图", "一目均衡表", "RSI", "MACD", "布林带", "谐波形态", "艾略特波浪", "缠论", "分型", "笔", "中枢", "Smart Money", "BOS", "FVG", "海龟交易", "海龟信号", "K線形態", "蠟燭圖", "一目均衡表", "纏論", "ichimoku", "candlestick pattern", "K线形态识别", "形态识别", "识别K线", "识别形态", "harmonic", "Elliott Wave", "chan theory", "turtle trading", "SMC", "technical indicators", "技術分析", "海龜交易", "海龜信號", "諧波形態"

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