「sca」の検索結果

Scan the current codebase to identify and categorize every public-facing page (landing pages, product/feature pages, solutions, pricing, resources, blogs, case studies, about, legal) and produce a single authoritative inventory document. Use this skill whenever the user asks to "init overgrow", "set up overgrow", "scan the site", "inventory the pages", "categorize pages", "map the site", or whenever any other overgrow skill needs a baseline page map and none exists yet. Output is a structured markdown inventory at `.overgrow/inventory.md` that all other overgrow skills read from.

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 design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.

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 "test our messaging before we scale it", "design a message-market-fit panel", or "run a 5-second comprehension test on our new tagline"; produces a message-test design spec — hypothesis, panel and recruit criteria, comprehension / 5-second / message-market-fit (Wynter-style) protocols, stimulus set drawn from the canon, success thresholds, and a stop/revise decision rule — for the TALE Evaluate phase so the message is validated before any paid scale. It designs the test; it never runs the experiment or adjudicates a claim. Not for running the panel or A/B experiment — use send-experiment-designer or ad-test-designer; not for analyzing the results — use performance-analyzer; not for authoring the message itself — use message-system-architect. 消息测试/理解度测试/面板设计/五秒测试/消息市场契合

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 "triage our comments, DMs, and mentions", "draft replies to this thread", "can we repost this fan post", or "set up inbox SLAs and an escalation path"; produces a ranked triage queue with register detection (sincere / ironic / performative / parasocial, sentiment-inversion table included — "this is so bad" under a comedy register is praise), a commenter taxonomy (troll monitor-only / rager / misguided / unhappy-customer / advocate) with a response-tier ladder and per-channel SLAs, an escalation matrix ending at the crisis path, a moderation ladder plus house rules for owned spaces, and a UGC curation-and-rights mode whose dated permission entries route to the channel registry — every reply is a ranked DRAFT a human posts; nothing is ever auto-sent. Not for launch-window feedback triage — use launch-feedback-synthesizer. 评论私信提及分诊/语域识别/回复草稿/UGC授权

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。

Scan agent skills for security issues before adoption. Detects prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks.

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。

Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

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。

Collect and verify Google Street View exterior references for a building reconstruction, preserving panorama identity, imagery dates, attribution and viewpoint separately from calibrated scan evidence.

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 cataloging or annotating visible construction in photographs or scan RGB, especially before registration or while the base model may be replaced.

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-level guidance for Flutter production applications: architecture decisions (Clean/Layered/Hexagonal/Feature-First), advanced state management (BLoC/Riverpod/GetX), performance optimization (eliminating jank, memory profiling, reducing rebuild overhead), code review with design pattern enforcement, scalability assessments, native platform integration (MethodChannel/EventChannel/FFI), complex UI challenges (custom render objects, slivers), testing strategies (unit/widget/integration/golden), CI/CD pipeline architecture, build optimization, and accessibility compliance. Triggers: 'architecture decision', 'design pattern', 'performance issue', 'code review', 'production problem', 'scaling concerns', 'best practices', 'technical debt', 'refactoring strategy'. Essential for complex enterprise apps, critical production debugging, architectural refactors, or when choosing between competing technical approaches.

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。

Implements data visualization charts in Flutter using the fl_chart package (v1.2.0). Supports LineChart, BarChart, PieChart, ScatterChart, RadarChart, and CandlestickChart with implicit animations, touch interactivity, and pan/zoom transformations. Use when building any Flutter chart, graph, or data visualization — including line graphs for trends, bar charts for comparisons, pie/donut charts for proportions, scatter plots for distributions, radar charts for multi-axis comparisons, or candlestick charts for financial OHLC data. Also use when customizing chart axes, titles, tooltips, grid lines, touch callbacks, chart animations, or chart zoom/pan behavior.

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。

This skill should be used when the user asks to \\\"analyze competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces",...

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。

Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD 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。

Coordinate multi-layer security scanning and hardening across application, infrastructure, and compliance controls.

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。

Scaffold project/workspaces, apply base structure and configs, and verify dev server startup gate

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。

Cascade approved evolution changes through downstream layers, assess impact, run consistency checks, and write evolution audit record

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。

Runbook skill for failures: cron error, PA failure, cascade, gateway disconnect, semantic DB stale. Walks: detect → classify → diagnose → notify → log. Replaces ad-hoc failure handling. Triggers: "cron failed", "X is broken", "cascade", "incident", "gateway down", "PA failure".

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 working with Aws Inspector — aWS Inspector vulnerability management and finding analysis. Covers Inspector v2 coverage, vulnerability findings, finding summaries, scan configurations, suppression rules, and coverage statistics. Use when auditing vulnerability posture, reviewing Inspector findings, checking scan coverage, or analyzing security vulnerabilities across EC2, ECR, and Lambda resources.

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 working with Aws App Runner — aWS App Runner service management and health analysis. Covers service inventory, deployment status, auto-scaling configurations, custom domain associations, VPC connector settings, and observability configurations. Use when inspecting App Runner services, debugging deployment failures, reviewing scaling behavior, or auditing service configurations.

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 working with Semgrep — semgrep static application security testing (SAST). Covers code scanning, custom rule creation, CI integration, autofix capabilities, multi-language support, and vulnerability triage. Use when scanning source code for security vulnerabilities, creating custom detection rules, or integrating SAST into CI pipelines.

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。

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

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。

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

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。

AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for SQL injection, XSS, command injection, exposed API keys, hardcoded secrets, insecure dependencies, access control issues, or any request like "is my code secure?", "review for security issues", "audit this codebase", or "check for vulnerabilities". Covers injection flaws, authentication and access control bugs, secrets exposure, weak cryptography, insecure dependencies, and business logic issues across JavaScript, TypeScript, Python, Java, PHP, Go, Ruby, and Rust.

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。

Find one insight that eliminates multiple components - "if this is true, we don't need X, Y, or Z

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。

DevOps infra v2 — VPS, Docker, Coolify, CI/CD, monitoring, Tailscale

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。