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概要と使いどころ
When the user wants to improve E-E-A-T, add trust signals, or optimize for expertise and authority. Also use when the user mentions "E-E-A-T," "E-E-A-T signals," "experience expertise authority trust," "author bio," "YMYL," "trust signals," "expertise signals," "authority signals," "citations," "references," or "credibility." For headings, use heading-structure.
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。
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
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。
Set up signal capture for a Simulink Real-Time application using `slrealtime.Instrument`. Use when choosing which signals a real-time application captures and where the data goes — test-pointing or canvas-badging a signal before build (`TestPoint`, `DataLogging`), constructing an Instrument from an `.mldatx`, calling `addSignal`, `addInstrumentedSignals`, `addFileLogSignals`, `validate`, `connectCallback`, `copy`, or `generateScript`, attaching an instrument to `tg.Instruments` via `addForFileLog`, `addForSDI`, or `addForMATLAB`, setting up live-streaming signals, dynamic file-log workflows, or persisting an instrument as M-code. Selects and routes signals only — not for configuring, building, running, or connecting applications onto targets.
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。
Deprecated alias. This skill was renamed to `deepline-scoring`. Use when a user or script still invokes `/niche-signal-discovery`: immediately load and follow the `deepline-scoring` skill instead. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals.
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 searching for buying signals, detecting intent data, scoring prospect readiness, or monitoring accounts for trigger events. Triggers: 'scan for signals', 'find buying signals', 'who is ready to buy', 'intent signals', 'signal scoring', 'account signals'.
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。
State management for Angular 18-21: signals (signal/computed/effect), services-as-state, NgRx Store + Effects + Selectors, NgRx Component Store, NgRx Signals (newer signal-based store). RxJS essentials — operators, async pipe, takeUntilDestroyed, signal/observable interop. Use this skill to: - Pick the right state tool (signals / services / NgRx variant / vue-query equivalent). - Use signals correctly (signal/computed/effect — when each). - Build a Pinia-style service-as-state singleton. - Set up NgRx Store + Effects + Selectors. - Use RxJS without leaking subscriptions (async pipe, takeUntilDestroyed, Subject patterns). - Bridge signals ↔ observables via toSignal / toObservable. Do NOT use this skill for: - General Angular conventions (see angular-conventions). - Routing state (see angular-routing). - Form state (see angular-forms). - Testing state (see angular-testing).
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。
Per-trade smart-money signals — each result is a discrete buy or sell event from a tracked smart-money wallet, with trigger price, current price, max gain since trigger, and exit rate. BSC and Solana only. Use for: "smart money buy signal on $X", "any whale just bought $Y", "alpha signals in the last hour", "copy-trade-worthy signals", "trigger price and max gain on these trades", "on-chain trading signals from smart money".
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 event-driven, decoupled Godot 4.7 gameplay with signals and node groups: declare and emit custom signals, connect with Callables (incl. bind/one-shot), and broadcast to many nodes via groups and call_group. Use when wiring node communication in a Godot project, replacing tight references with signals, emitting/connecting events, or porting 3.x connect("sig", self, "method") code.
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。
Angular is opinionated and comprehensive - it gives you everything: routing, forms, HTTP, dependency injection, testing. The learning curve is steep, but once you're in, you move fast. The structure it enforces is why enterprises love it. This skill covers Angular 17+, standalone components, signals, the new control flow syntax, and modern Angular patterns. Key insight: Angular's power is in its DI system and RxJS integration. Master those, and everything else follows. 2025 lesson: Standalone components are the future. NgModules aren't going away, but new projects should start standalone. Signals are Angular's answer to fine-grained reactivity - learn them. Use when "angular, angular component, angular service, angular routing, angular forms, rxjs, ngrx, angular signals, standalone component, angular ssr, angular, typescript, frontend, spa, enterprise, rxjs, signals, standalone" mentioned.
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。
Checkable-ish surface presentation signals a reviewer notices first — duplicate/near-identical tables, leftover pipeline/template strings, too-few or LLM-looking figures, and page-padding. AUXILIARY ONLY and weak by design: a deterministic pass (tools/check_presentation.py — dup-table + pipeline-artifact) plus a fresh cross-model GROSS-cases-only semantic pass (thin-float, LLM-figure, page-padding), every above-info finding span-anchored to the evidence ledger (claims.json). The adjudicator CAPS everything at minor (SURFACE_ONLY_SKILLS + SURFACE_PATTERNS) — these contribute at most SOFT_FLAGS, never a HARD verdict — default false_positive_risk:high. NOTE: the pure AI writing-STYLE impressions (AI-flavor prose, defensive 'not-X-but-Y' hedging, narrative-arc, jargon-stuffing, invented codenames) MOVED to the zero-verdict-weight AIS track — for those use skills/ai-style-impressions, NOT this. Emits presentation-signals.findings.json; NEVER computes the verdict. Triggers: "presentation signals", "surface check", "duplicate tables", "排版信号".
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。
Focused Signals scout for PostHog projects running Replay Vision scanners — the standing LLM probes that watch session recordings and write `$recording_observed` events. Watches two promises: that enabled scanners are actually observing (throughput / success-rate cliffs, exhausted quota — a silent watch gap), and that what the scanners see in aggregate gets surfaced (a monitor's `yes`-rate or a scorer's score stepping away from its own baseline, a classifier tag or a recurring summarizer theme concentrating across many sessions). It is the agentic pull complement to the per-session push path: scanners with `emits_signals` already emit one signal per session into this same inbox, so this scout never repeats them — it adds the cross-session shape the per-session probe can't see. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet.
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。
General Signals scout for PostHog projects. Cross-product explorer that scans a team's project and emits findings into the Signals inbox. Sibling signals-scout-* specialists each watch a single product surface in depth; this scout looks for cross-product correlations and explores the surfaces no specialist covers. Each scout runs on its own schedule (default hourly), so general fires independently of the specialists over time.
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。
How to explore and make sense of PostHog Signals scouts — the scheduled agents that scan a project and emit findings into the Signals inbox. Use when a user wants to understand what scouts they have, how each one is behaving, and whether the fleet is actually working. Covers surveying the fleet and its schedules, reading recent scout runs and drilling into a single run's reasoning, inspecting the durable scratchpad memory the fleet has built up, tracing a run to the findings it emitted, and assessing a scout's health and performance over time (cadence, success rate, emit rate, signal-to-noise). Read-only and exploratory — to write or tune a scout, use `authoring-signals-scouts` instead. Trigger on "what are my scouts doing", "how is my <x> scout performing", "show me recent scout runs", "why did this scout find/emit nothing", "what has the fleet learned", "explore scout run <id>", "is my scout working".
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。
How to author, edit, and adapt PostHog Signals scouts — the scheduled agents that scan a project and emit findings into the Signals inbox. Use when a user wants to customize a canonical scout for their own setup (narrow its scope, retune its thresholds, add disqualifiers), tweak a scout's schedule or dry-run posture, or write a brand-new scout from scratch for a specific use case (a custom event, a product surface no canonical scout covers). Covers the scout SKILL.md anatomy, the emit contract, the dedupe + scratchpad-memory conventions, the per-team skills-store path vs the canonical in-repo path, and the emit-and-inspect test loop (with dry-run as an optional safety net). Trigger on "write/edit/customize a signals scout", "new scout for X", "tune my scout schedule", "make a scout that watches <event>".
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。
The live fieldwork layer for psycho-logic — go look at the actual target market NOW instead of reasoning from your training-data stereotype of it. Use when a psycho-logic move needs grounding in a specific place: the user asks 'what do competitors in [region/country] actually do', 'what's the real price band / norm here', 'how do local leaders position themselves', 'research this market before we localise', 'what signals trust to buyers in X', or is about to launch/adapt in a market you haven't studied. Runs structured web research in the local language — local competitors and their signals, price bands, category conventions, review/trust sources, local terminology, taboos and regulations — and synthesises a compact perception profile the four moves consume. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic; pair with cultural-context (the lens that tells you what to look for). 日本語・中文の相談（「現地の実態を調べて」「调研当地市场」）にも使う。
Angularの画面やサービスを作り、状態管理・フォーム・画面遷移の設計を支援します。使用バージョンに合わせて実装方針を選び、テストやビルド確認まで扱います。
Build lean, opinionated products using the 37signals philosophy from "Getting Real", "Rework", and "Shape Up". Use when the user mentions "Getting Real", "Rework", "Shape Up", "37signals", "Basecamp method", "six-week cycles", "fixed time variable scope", "appetite vs estimates", "betting table", "breadboarding", "fat marker sketch", "build less", "underdo the competition", "opinionated software", "we have too many meetings", "how do we ship faster", or "stop overbuilding". Also trigger when cutting scope to ship sooner, running a small team, or avoiding long-term roadmaps. Covers shaping, betting, building, and the art of saying no. For MVP validation, see lean-startup. For design sprints, see design-sprint.
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 this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.
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 3GPP-compliant 5G NR downlink and uplink baseband waveforms. Use to create NR signals, test model (TM) waveforms, fixed reference channels (FRC), test and measurement (T&M) signals, or test vectors for conformance testing. Covers configuring data, control, and broadcast channels and signals: PDSCH, PUSCH, PDCCH, PUCCH, SRS, SSBurst, CSI-RS, DM-RS, PT-RS, CORESET, and BWP parameters including bandwidth, subcarrier spacing (SCS), modulation (QPSK, QAM), numerology, FR1, FR2, TDD, FDD, and multi-bandwidth-part setups. Use for signal generation, RF instrument playback, or IQ baseband synthesis. Requires 5G Toolbox.
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。
Emit the content signals reimagine-it reads from an HTML file — title, anchors, proper nouns, dates, numbers, emails, links, source hex colors, and the derived palette — as JSON without generating a redesign. Use when the user says /reimagine-it extract, "what does the engine see in this page", "extract the palette", "pull the facts from this page", or wants content analysis for research, migration, or design-system work. CLI: npx reimagine-it extract -i page.html -o signals.json. Part of the reimagine-it Content-Derived Design suite.
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。
Evaluates factor timing strategies with macro regime indicators, valuation spreads, and momentum signals for factor rotation. Use when analyzing factor timing, evaluating rotation signals, or designing tactical factor allocation.
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。
NgRx SignalStore patterns for Angular state management. Use when managing client state with Angular Signals, composing store features, handling entities, or integrating RxJS effects.
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。
Fri→Fri community signals routine across CopilotKit + AG-UI. Orchestrator that supervises subagents — Discord pull, GitHub pull, deep-read, reporter enrichment, Reddit Pulse — and synthesizes a Notion report under the Community Signals parent page. Triggers on "go", "weekly report", "community signals", "run routine".
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。
Focused Signals scout for PostHog projects using revenue analytics. Watches the derived revenue product for upstream failures (Stripe sync stalls, capture regressions), config drift (missing subscription property, currency mix surprises, broken Stripe↔person joins, deferred-revenue gaps), and goal-miss escalations. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet — no dependencies on other skills.
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。