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概要と使いどころ
Use when turning any content into clear, professional visualizations - board slides, reports, proposals, research summaries, training materials, technical diagrams, infographics, process flows, timelines, benchmarks, waterfall charts, or data-backed visual specs for any audience.
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。
Computes a numeric or categorical answer to a quantitative data-science question by cleaning and analyzing local data files (CSV, Excel, TSV, and scientific formats .npz/.fits/.h5) with pandas, numpy, and scipy. Use whenever a task ships its own dataset (in whatever local directory it provides) and asks you to derive a value via statistical, geospatial, temporal, ratio, percentage, growth-rate, correlation, signal-processing, orbital, or forecasting analysis. Spans domains including archeology (demographics, paleoclimate proxies, radiocarbon dating, historical conflicts); biomedical/bioinformatics (tumor histology, genes, proteins, peptides, genomic variants); environmental (water quality, bacterial/Enterococcus exceedance, rainfall correlations, environmental justice); legal/consumer (fraud, identity theft, consumer complaints by state/metro); wildfire (incidents, causes, suppression costs, acres burned, fatalities, geospatial intersections); and astronomy/heliophysics/space weather (satellite telemetry TLE/Swarm/SP3, indices OMNI/GOES, solar activity, atmospheric density, orbital mechanics, forecasting).
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。
Answer user questions about QwenPaw installation and configuration: first locate and read local documentation, then distill the answer; if local information is insufficient, fall back to the official website 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。
Applies the dialectical reasoning and intellectual humility of Socrates (ancient Greek philosopher, 470-399 BCE). Use this skill whenever the user is grappling with fundamental definitions, moral dilemmas, educational approaches, self-reflection, or making high-stakes ethical decisions. Trigger this skill when encountering topics like virtue, justice, the pursuit of truth, questioning assumptions, coaching, or when the user seems overly confident in unexamined beliefs. It helps dismantle false assumptions through probing questions and redirects focus toward the "care of the soul" and objective truth over external validation or material success.
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。
Suede Slop Stop: Suede Labs context-aware anti-slop pass for finished prose. Find or remove generic filler, manufactured emphasis, false agency, formulaic structure, chat and draft residue, and formatting applied by rule, without flattening the author's voice. Use before copy, a README, an email, a social post, or a doc ships; after a long assisted-writing session; or for a findings-only slop audit. NOT FOR: writing new copy (use suede-copy); deciding whether a person or model wrote text; changing or certifying facts, which require primary 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。
Suede AI MCP release QA, scoped to this pack's own server (mcp/suede-skills-mcp.mjs) and its catalog, install, and docs surface. Runs the full JSON-RPC lifecycle against a live server (initialize, notifications/initialized, ping, tools/list, tools/call, resources/list, resources/read, prompts/list, prompts/get), plus protocol negotiation, closed input and output schemas, tool annotations, structuredContent with text fallbacks, malformed-input probes, clean stdio, catalog-to-folder agreement, and install-path language. Use when the MCP server, mcp/catalog.json, a tool, resource, or prompt definition, or the MCP install docs change, or before publishing an MCP release. A check that did not run against the live server is a FAIL, not a skip. NOT FOR: a generic third-party MCP server, which this skill's hardcoded surface does not describe; fixing or testing the public install path itself (use suede-launch-packaging).
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 verifying a running application end-to-end through its real interface — a web UI, a CLI, or a TUI — by writing and executing agent-run "scenario cards" against a freshly built instance with falsifiable assertions. Trigger on "test it end to end", "prove the UI actually works", "write/run a scenario", or after a change touches a user-facing surface that unit tests can't fully cover. Not for unit tests, pure code review, or API-only checks.
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, modify, audit, repair, optimize, debug, and deploy agents with Agentforce Agent Script. TRIGGER when: user creates, reviews, or changes .agent files or aiAuthoringBundle metadata; asks to fix AgentScript, audit an existing agent, run an AgentScript health check, common-pitfall review, or baseline-versus-candidate repair loop; changes a response, action, subagent, route, state flow, or Agent Spec; previews, debugs, deploys, publishes, or tests agents; uses sf agent generate/preview/publish/test; or manages Agentforce MCP servers, tools, assets, or authentication. DO NOT TRIGGER when: Apex, Flow, Prompt Template, Experience Cloud, or general Salesforce CLI work is unrelated to Agent Script; or the primary input is a production session or trace ID rather than an agent artifact.
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 reviewing Go changes - net/http and Fiber handlers, database/sql and GORM queries, os/exec, filepath and os.Root, html/template, crypto, TLS and SSH clients, JSON binding
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 reviewing Java or Kotlin server changes on Spring or Quarkus - security config and method security, JPA/JPQL and JdbcTemplate queries, request binding, deserialization, XML parsers, SpEL, templates, Actuator, JNDI and reflection
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 reviewing Node.js or TypeScript server code - Express/Fastify/Nest handlers, Next.js server actions and route handlers, child_process, ORM raw queries, prototype pollution, template engines, JWT and outbound HTTP clients
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 a candidate finding falls into a noisy category - the do-not-report list, the precedents that settle recurring edge cases, and the narrow exceptions where an excluded category still counts
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 reviewing Python changes - Django, Flask and FastAPI handlers, subprocess, SQL, Jinja2, format strings, and data/ML code that loads pickles, models, notebooks or remote model 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。
Use when you have a candidate security finding and before it goes in a comment - restate it, prove reachability, impact and a concrete exploit, apply triage dismissals, then the self-refute pass naming attacker and victim
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 reviewing game code in C#, GDScript or C++ (Unity, Godot, Unreal, custom engines) - client vs server authority, RPC and packet validation, in-app purchases and economy, save and replay files, mod and script loading, secrets in client builds
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 an editor MCP server (unity, godot, unreal, blender) or the browser MCP shows up in your tool list - what each one can observe or change, how to check it is attached to YOUR task workspace, why the repo's tests still decide, the Blender code-execution caution, and the headless fallback when none is connected.
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 or running Unity tests - Unity Test Framework EditMode vs PlayMode, test assembly definitions, testing plain C# and ScriptableObjects, PlayMode scene/physics/input tests, batchmode CLI with result XML, coverage, and the dotnet test fallback when no editor is installed.
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 tools from the jupyter, duckdb, dbt, mlflow, huggingface or postgres MCP servers appear in your tool list, or before reaching for one — what each is good for, what it can damage, and the CLI fallback when it is not connected
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 you are about to hand off any number, table, chart or analysis someone will act on (a metric query, a dbt mart, a report, an experiment readout) — the pre-delivery checklist for data quality, calculation, reasonableness and presentation, and the pitfalls that produce plausible wrong numbers
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 Java is chosen but Quarkus does not fit - build the service with Spring Boot using the same clean layering, only when a required library lacks a Quarkus extension or the repo already standardizes on Spring
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。
Deploy, manage, and debug Kubernetes in production — Deployments, Services, Gateway API, Service Mesh (Istio/Linkerd/Cilium), eBPF observability (Cilium Hubble), security hardening (Pod Security Standards, OPA/Kyverno, seccomp, runtime security with Falco/Tetragon), Helm, HPA, PDB, topology spread, and debugging. Use when user asks to write K8s manifests, deploy to a cluster, debug pods, set up Gateway API, configure autoscaling, or harden cluster security. Do NOT use for Dockerfiles (use docker), CI/CD pipeline design (use ci-cd), or Terraform infrastructure (use terraform).
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。
Reescreve textos em português brasileiro para soarem mais humanos e naturais, reduzindo padrões típicos de escrita gerada por IA sem alterar fatos, argumento ou intenção. Use quando o texto em PT-BR parecer genérico, burocrático ou gerado por IA, ou quando o usuário pedir para "humanizar", "dar vida", "tirar cara de IA", "remover AI slop" ou "reescrever com voz". Use também para ESCREVER DO ZERO em português qualquer texto que uma pessoa vai assinar ou publicar (post, artigo, e-mail, proposta, release, README, bio, descrição de produto): nesse caso a lista de padrões funciona como filtro de saída. Para textos em inglês, use a skill-irmã `human-ai`. Também trabalha a partir de notas e transcrições do autor e faz perguntas pontuais quando faltam dados essenciais.
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。
Onboarding-and-switching playbook for SMB Product-Builder products. Defines the first-run experience that turns a prospect leaving an incumbent (ServiceTitan/Toast/Mindbody/Shopify/QuickBooks) into an activated user — import-first onboarding, the activation milestone, sample-data fallback, and the time-to-first-value target. Applied by migration-import-engineer and architect/pm so onboarding is designed as a funnel, not an afterthought. Our whole wedge is "low switching cost"; this skill makes that real on day one.
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。
Unified image-generation engine for the product-shots ecosystem. Dispatches to the right model family (OpenAI gpt-image-2 / Gemini gemini-3-pro-image-preview Nano Banana Pro) with one parameterised script for text-to-image and image-to-image. Primary backend: OmniMaaS / Cloubic gateway (https://api.omnimaas.com/v1); also supports any OpenAI-SDK-compatible gateway via fallback env vars. Auto-resizes oversized reference images to prevent edge-proxy timeouts. Use when the user says "generate an image", "make a picture", "create a visual", "render this", "edit this image", "做一张图", "生成图片", "改这张图" — or when invoked as the image-generation backend by another product-shots skill (main-image / detail-page / ad-creative / social-post / multi-angle). NOT a creative-direction skill: takes a prompt + optional reference images, returns a file path.
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。