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概要と使いどころ
Builds citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.
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。
Professional content generation system with a GSD-style phased workflow, integrated SEO optimization (claude-seo), and anti-AI auditing (humanizer). USE THIS SKILL whenever the user asks to write, draft, create, generate, or produce ANY content — including blog posts, articles, LinkedIn posts, Facebook posts, Twitter/X tweets or threads, Instagram captions, email newsletters, email campaigns or sequences, landing pages, product pages, web pages, sales pages, sales funnels, case studies, testimonials, product descriptions, or SEO metadata. Also triggers on: "/writer:discuss", "/writer:plan", "/writer:execute", "/writer:verify", "/writer:ship", "/writer:next", "/writer:profile-create", "/writer:profile-view", "/writer:profile-edit", "/writer:status", "/writer:help", "/writer:update" — or any request to manage a writer profile or create marketing materials. ALWAYS use this skill even for quick, casual content requests like "write me a LinkedIn post about X" or "draft a tweet thread." The profile and phased workflow produce significantly better output than ad-hoc generation.
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。
Professional content generation with phased workflow (discuss→plan→execute→verify→ship), SEO optimization, and anti-AI auditing. Multi-profile support for unlimited brands. USE for: blog posts, LinkedIn, Twitter/X, Facebook, Instagram, email newsletters, landing pages, sales pages, case studies, product descriptions, SEO metadata. COMMANDS: /writer:discuss, /writer:plan, /writer:execute, /writer:verify, /writer:ship, /writer:next, /writer:profile-create, /writer:profile-list, /writer:profile-use, /writer:profile-view, /writer:profile-edit, /writer:status, /writer:help ALWAYS use for content requests like "write me a LinkedIn post" or "draft a blog article."
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。
Cloud control-plane reconnaissance for AWS, Azure/Entra, GCP, and Alibaba Cloud: identity, IAM/RAM, trust, resources, metadata, and managed-Kubernetes cloud-side boundary. Recon only — no policy changes, no privilege escalation. Operator may select /cloud-attack or /k8s.
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。
Regenerate `.sqlx/` cached metadata when adding or modifying `sqlx::query!`, `sqlx::query_as!`, or `sqlx::query_scalar!` macros.
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。
Retrieves metadata for a specific Stitch project — title, theme, create/update time. Use to inspect a project before generating new screens. Do NOT use this if you already have a screenId — use stitch-mcp-get-screen instead.
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, moving or auditing any .md in imp - deciding which file a paragraph belongs in, adding a doc, fixing a stale claim, or when docs_lint.py fails in CI. Covers the four reader layers (L0 README / L1 operators / L2 kernel devs / L3 agents), the HTML-comment metadata header, [PROV:] provenance, the single-source-of-truth map, generated perf blocks, which numbers may appear in prose, plan-doc closure. Triggers on "which doc does this go in", "docs lint failed", "add a doc", "this claim is stale", "update the README", "PROV block", "layer", "STALE.md". Do NOT use for the CHANGELOG or a release body (shipping-prs), or for code-comment accuracy (codebase-audit).
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。
Agent task delegation patterns — spawn protocols, handoff metadata, drain gate, parallel limits, and model selection for multi-agent orchestration
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。
Create custom Semgrep rules for detecting project-specific vulnerabilities, enforcing coding standards, and building domain-specific security checks with proper testing and metadata.
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。
Hunt cloud misconfigurations exposed externally — open S3/GCS buckets, exposed IAM-tied EC2 metadata, Cognito misconfig, GitHub Actions secret leakage, exposed Kubernetes API, public Elastic / Kibana / Mongo, Firebase RTDB rules, weak AWS access keys discovered in JS/mobile. Use when leveraging leaked credentials or hunting cloud surface in scope.
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。
Hunt Server-Side Request Forgery (SSRF) — internal network access, cloud metadata exploitation, gopher/file/dict protocol abuse, and 11 IP-filter bypass techniques. Use when an endpoint accepts a URL, hostname, or file path as input.
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。
Pre-submission audit for an App Store release — runs the pre-flight checks and walks the three privacy surfaces, the high-frequency App Review rejection guidelines, and metadata/release-option choices. Use before submitting an iOS app for App Review.
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 creating or editing notes inside an Obsidian-compatible vault, to write correct Obsidian Flavored Markdown — wikilinks, embeds, callouts, YAML properties (frontmatter), tasks, highlights, and block references. Use whenever writing .md notes for a second brain / Obsidian vault so links resolve and metadata is queryable.
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。
Complete App Store Optimization toolkit - generate metadata in any language, analyze competitors, optimize keywords, set up IAPs/subscriptions, and submit to App Store Connect via direct API
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。
Manage Claude Code sessions — search by topic or ID, browse recent sessions with full metadata (tags, summaries, titles, cost), view title/nickname history timelines, resume in Ghostty tabs, spawn interactive or headless sessions, monitor live sessions, and bootstrap new setups. Triggers on resume session, find session, list sessions, recent sessions, spawn session, session history, what was I working on, open in ghostty, title history, session nicknames.
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。
Search and download images from 15 APIs in parallel (Openverse, Pexels, Pixabay, Met Museum, Cleveland Museum, Art Institute of Chicago, Getty Museum, NASA, Rijksmuseum, Wikimedia Commons, Unsplash, Smithsonian, Europeana, Iconify, Pollinations AI). Supports license filtering, presets (military, museum, stock), cached results, and bulk download with metadata sidecars. Triggers on find images, stock photos, public domain artwork, museum images, CC-licensed, NASA photos, icons.
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 deterministic technical SEO and schema.org guidance for crawlable public pages. Use this skill when the user asks for title and meta description rules, canonical and hreflang tags, JSON-LD schema, NewsArticle, Article, TechArticle, BreadcrumbList, WebSite, Organization, Person, OpenGraph, Twitter cards, sitemap, news-sitemap, RSS, robots.txt, llms.txt, publisher logo, ImageObject, or metadata templates that must match visible content.
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 local coding agent (Codex, Claude Code, Cursor, or similar) needs to operate Multica through the authenticated `multica` CLI: reading or updating issues, comments, metadata, labels, custom properties, subscribers, projects, agents, squads, runtimes, repos, skills, autopilots, attachments, or workspace state; searching issues; inspecting or cancelling agent runs; replying to a Multica issue from an external agent; creating or triaging issues; checking linked pull requests; or safely handling Multica mention/status side effects without relying on the Multica hosted agent runtime.
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。
Draft, expand, revise, structure, and maintain a full Islamic University of Technology BSc thesis from source documents using the local iutbscthesis LaTeX template. Use when writing or editing thesis metadata, front matter, abstract, chapters, related works, methodology, results, discussion, conclusion, citations, appendices, figures, tables, code listings, or compile guidance for main.tex. Also use when the user expects an AI agent to turn papers, notes, PDFs, LaTeX sources, bib files, data tables, and assets into a substantial thesis manuscript chapter by chapter without requiring repeated babysitting.
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。
Produce a truthful Japanese App Store metadata pack and app-name shortlist in twelve minutes without a multi-agent research round. Use for a live launch sprint, fallback ASO copy, app naming under a hard deadline, or when local product evidence is available but market research is intentionally deferred.
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。
Register trained models in MLflow Model Registry with version control, implement stage transitions (Staging, Production, Archived) with approval workflows, and manage model lineage with comprehensive metadata and deployment tracking. Use when promoting a trained model from experimentation to production, managing multiple model versions across development stages, implementing approval workflows for governance, rolling back to previous versions, or auditing model changes for compliance.
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。
Evolve an existing skill by refining its content in-place or creating an advanced variant. Covers assessing the current skill, gathering evolution requirements, choosing scope (refinement vs. variant), applying changes, updating version metadata, and synchronizing the registry and cross-references. Use when a skill's procedure steps are outdated, user feedback reveals gaps, a skill needs a complexity upgrade, an advanced variant is needed alongside the original, or related skills are added and cross-references are stale.
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。
Evolve an existing team composition by refining its structure in-place or creating a specialized variant. Covers assessing the current team against template and coordination patterns, gathering evolution requirements, choosing scope (adjust members, change coordination pattern, split/merge teams), applying changes to the team file and CONFIG block, updating version metadata, and synchronizing the registry and cross-references. Use when a team's member roster is outdated, coordination pattern no longer fits, user feedback reveals workflow gaps, a specialized variant is needed alongside the original, or agents have been added or removed from the library affecting team composition.
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。
Evolve an existing agent definition by refining its persona in-place or creating an advanced variant. Covers assessing the current agent against best practices, gathering evolution requirements, choosing scope (refinement vs. variant), applying changes to skills, tools, capabilities, and limitations, updating version metadata, and synchronizing the registry and cross-references. Use when an agent's skills list is outdated, user feedback reveals capability gaps, tool requirements have changed, an advanced variant is needed alongside the original, or the agent's scope needs sharpening after real-world use.
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。