「fea」の検索結果

Extract features from signals collected on rotating machinery components, including motors, pumps, fans, gears, bearings, and shafts. Signals can include vibration, electrical, or environmental sensor measurements. Use when developing and deploying condition monitoring and fault detection applications for rotating machinery, including industrial machines, electrical vehicles, internal combustion engines, turbines, and drive trains.

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。

Discover related plans for the current task: same feature folder full depth, other features active-only, general-plans active. Like vc-context-discovery but for plan artifacts.

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。

Implement a feature safely end-to-end in this repository. Use when adding or changing functionality across backend, frontend, or MCP with required verification and documentation updates.

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。

MANDATORY for every coding agent (Claude Code, Codex, or any other) — keep this repository's documentation in sync after any change to behavior, configuration, interfaces, events, schema, or features. Use automatically at the end of change-sets that alter an env var, event type, hook or state behavior, API, schema, WebSocket message, MCP tool, CLI command, or user-facing feature, and whenever the user asks to update documentation.

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。

结构化新功能交付工作流，适用于显式 new feature、从需求到实现的一站式功能开发或恢复未完成任务场景；通过项目内 .codex/tasks/ 持久化状态。

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。

Audit and generate in-app user guidance — onboarding flows, empty states, tooltips, feature tours, contextual help, defaults, and inline hints. Browses the app to find where new users would get stuck, then produces the actual content and code to fix it. Pairs with ux-audit: audit finds problems, this skill builds the solutions. Triggers: 'onboarding', 'help content', 'empty states', 'user guidance', 'first run experience', 'feature tour', 'app is confusing', 'new user experience', 'make the app welcoming'.

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 actually instrument product analytics correctly. Event taxonomy, property design, naming conventions, schema versioning, identity stitching, funnel design, retention cohorts, North Star metric selection, dashboard hygiene, instrumentation debt, and the failure modes that produce data nobody trusts. Triggers on product analytics setup, event taxonomy, tracking plan, instrumentation, schema versioning, North Star metric, retention cohorts, funnel design, naming conventions, instrument new feature, audit existing analytics, dashboard reconciliation, instrumentation debt, Mixpanel setup, Amplitude setup, PostHog setup, warehouse-native analytics. Also triggers when the team has data but cannot trust it, or when designing instrumentation for a new feature, or when auditing an existing setup that has drifted.

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。

Designing in-product tours, tooltips, and contextual help that teach product capabilities without becoming friction. Trigger logic, tour architecture, contextual placement, completion tracking. Honest about tooltip-spam (visual noise that users develop blindness to), one-and-done (help invisible at the moment of need), and contextual-when-needed (surfaces help at the moment friction occurs) patterns. Triggers on product tour, in-product tooltip, contextual help, walkthrough, feature tour, hint system, in-app guidance, tour platform. Also triggers when feature adoption is low, when users miss key product capabilities, or when an in-product help system is being scoped for the first 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。

The Jobs-to-be-Done framework as applied product methodology. Job statements, struggling moments, hire and fire criteria, the difference between feature-thinking and job-thinking. Honest about where JTBD adds clarity (discovery, prioritization, positioning) and where it becomes performative ritual (job-statement workshops that do not drive decisions, persona-theater disguised as JTBD). Triggers on jobs-to-be-done, JTBD, job statements, struggling moments, hire criteria, fire criteria, switch triggers, functional emotional social jobs, outcome-driven innovation. Also triggers when a team is over-relying on feature-request lists or persona archetypes that do not drive product decisions, when a positioning conversation needs the framing JTBD provides, or when discovery is producing outputs that do not connect to product 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。

Operational discipline for feature flags as production infrastructure. Flag types, naming, targeting rules, rollout strategy, lifecycle, governance, stale flag management, and the technical debt patterns that bite teams who weren't deliberate about it.

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 the user turn their Retentioneering ideas, friction reports, bug findings, or feature needs into high-quality upstream contributions: from capturing and validating the idea, through minimal reproductions and issue drafts, to preparing, testing, and submitting a pull request that follows this repository's conventions. Use when the user says they found a bug, wants a feature, wrote a workaround worth upstreaming, or asks how to contribute, open an issue, or make a PR to retentioneering-tools.

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。

Molecular featurization and chemical descriptor computation

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。

Conducts structured requirements workshops to produce feature specifications, user stories, EARS-format functional requirements, acceptance criteria, and implementation checklists.

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。

Implement features on branches from issue descriptions

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。

Clinical study operations — protocol structure, endpoint selection, eligibility design, sample-size and power planning, site feasibility, and documentation readiness. Use when planning, auditing, or costing a study.

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。

Plan and execute product launches and feature announcements: phased plans (alpha, beta, GA), channel strategy, Product Hunt playbooks, and post-launch momentum. Use when launching a new product or feature, or planning a Product Hunt launch.

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 "design an experiment", "build a predictive model", "run A/B test analysis", "perform causal inference", "engineer features", "evaluate model performance", "set up MLOps pipeline", "analyze time series", "calculate sample size", or "deploy a model to production". Expert data science covering statistical modeling, experimentation, causal inference, feature engineering, ML deployment, and advanced analytics with Python, R, and SQL.

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 writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, review-depth fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

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。

When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' 'product update,' 'how do I launch this,' 'launch checklist,' 'GTM plan,' or 'we're about to ship.' Use this whenever someone is preparing to release something publicly. For ongoing marketing after launch, see marketing-ideas. For the offer being launched (bonuses, guarantees, scarcity, naming), see offers.

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 a variation theory task using contrast, separation, and fusion to teach critical features of a concept. Use when students confuse similar concepts or fail to discern key distinctions.

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。

Expert blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.

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。

Navigation skill for genre project scaffolds: pick platformer/RPG/FPS (or other genre) then load matching template scripts and route gameplay fill to godot-genre-* skills. Use when bootstrapping architecture, bootstrap order, pause modes, PCK DLC, or feature tags — not for pasting FPS/inventory recipes. Keywords: project templates, bootstrap, Subsystem Locator, PCK, feature tags, PROCESS_MODE_ALWAYS, genre scaffold.

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。

Navigation skill for genre project scaffolds: pick platformer/RPG/FPS (or other genre) then load matching template scripts and route gameplay fill to godot-genre-* skills. Use when bootstrapping architecture, bootstrap order, pause modes, PCK DLC, or feature tags — not for pasting FPS/inventory recipes. Keywords: project templates, bootstrap, Subsystem Locator, PCK, feature tags, PROCESS_MODE_ALWAYS, genre scaffold.

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。

Expert blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.

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。