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Use when starting Claude Code projects, writing CLAUDE.md/spec.md, dispatching subagents, or requesting Agent Teams parallel development. Covers Spec-Driven Development, Context Engineering, and post-dev workflow.
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 build/test/lint before commit, PR, or completion claims. Runs verification pipeline in fresh subagent context with auto-repair. Triggers on /handoff-verify, pre-commit check, build verification, test validation.
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。
Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.
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。
Full-history Godot version migration hub. Use when upgrading any Godot project toward the library target (currently 4.7)—from 1.x/2.x legacy eras through 3→4 and hop-by-hop 4.x minors—or finding Domain Skill-scoped migration notes. Trigger keywords: upgrade Godot, migrate Godot version, Godot 3 to 4, Godot 2 to 3, upgrading_to_godot, version migration, breaking changes, convert-3to4, TileMapLayer, AnimationMixer, engine.cfg, project.godot.
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 movement decision router for chase, patrol, crowd, and bake choices on top of NavigationAgent/Server. Use when deciding node agent vs RID server, bake vs obstacle, layer masks, or retarget policy — not for engine navmesh recipes. Keywords: AI navigation, chase retarget, patrol, crowd RVO, bake vs obstacle, NavigationAgent decision tree.
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 runbooks, playbooks, and technical documentation for engineering teams. Use when the user wants to document a process, create a runbook, build operational docs, or formalize any repeatable technical procedure. Triggers on requests like "create a runbook for...", "document this process", "write a playbook", or any technical documentation request.
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。
Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", or "data-driven SEO".
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。
Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".
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 semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
EXPERIMENTAL — mutation testing with muter to measure whether tests actually assert anything: mutants that survive reveal assertion-free coverage. Advisory report only, never a merge gate. Use on engine/logic targets when coverage numbers look good but bugs still slip through.
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。
Generates a watermark overlay system for images and video with configurable positioning, opacity, tiling, and paywall integration for automatic removal on subscription or purchase. Use when user wants to add branding, attribution, or free-tier watermarks to visual 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。
Generate CloudKit sync infrastructure using CKSyncEngine with conflict resolution, sharing, and account monitoring. Use when adding iCloud sync to an iOS/macOS app.
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。
A first step in the data analysis of Mass Spectrometry (MS) based proteomics data is to identify peptides and proteins. With this respect the huge number of experimental mass spectra typically have to be assigned to theoretical peptides derived from a sequence database. Search engines are used for this purpose. These tools compare each of the observed spectra to all candidate theoretical spectra derived from the sequence data base and calculate a score for each comparison. The observed spectrum
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 knowledge for Azure Front Door development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring apex domains, rules engine, Private Link origins, TLS/WAF security, or tier migrations, and other Azure Front Door related development tasks. Not for Azure Application Gateway (use azure-application-gateway), Azure Traffic Manager (use azure-traffic-manager), Azure Load Balancer (use azure-load-balancer), Azure Web Application Firewall (use azure-web-application-firewall).
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。
Seller storefront analysis and competitive intelligence for Amazon. Analyzes seller revenue estimation, product portfolio strategy, growth trajectory, and market positioning. Reverse-engineer successful seller strategies and identify expansion opportunities. Use when the user asks about analyzing sellers, competitor seller analysis, seller revenue estimation, storefront analysis, seller strategy, or learning from successful Amazon sellers.
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。
Three-mode idea engine - generate collides the week's zeitgeist with what you can ship into scored wedges; validate viability-screens the idea backlog; memo writes evidence-backed startup memos.
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 prospect lists where the prospect is already one hop from the client, and write the line that says so. Seven members, each with its own source. Current-customer alumni is the priority member - everyone who ever worked at one of the client's customers or case-study companies and has since moved on. Triggers on "warm intro", "who do we know at that account", "they used to work at our customer", "alumni of our case study company", "shared investor angle", "who is in the same city as our rep", "did they visit our site". Outputs warm_intro_line plus a per-member evidence column.
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。
Compare reply rates, bounce rates, and positive reply rates broken down by inbox type (SMTP / Gmail / Outlook) for a Smartlead account. Use when you want to know "which inbox type delivers best" or when debugging unexplained deliverability differences across a mixed fleet. Operates via Smartlead API only (no database required).
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 searching for people/leads using the Prospeo Search Person API. It provides the correct API format, filter types, rate limiting patterns, and state-by-state crawling techniques to overcome the 25K result limit. Use when building lead lists, searching by job title/industry/location, or integrating with Prospeo.
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。
Turn the people who like and comment on a source account's LinkedIn posts (a competitor, or one of the client's own customers) into ICP-filtered prospect rows, with an optional copy-ready personalization line when the campaign asks for one. Triggers on "who engages with our competitors", "likers and commenters", "LinkedIn engagement list", "people commenting on competitor posts", "who engages with our customers' posts", "warm LinkedIn audience", "competitor engagers". Outputs one clean prospect row per engager; engagement_line only on request.
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。
Triage playbook for when cold email deliverability breaks. Decision-tree guidance for "I landed in spam", "bounce rate spiked", "domain blacklisted", "inbox blocked in warmup", "reply rate dropped". Tells you what to check first, what to fix, and how long the fix takes. Pair with /email-deliverability-audit for diagnosis.
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。
Smartlead API endpoint reference and patterns. Use for any Smartlead campaign, lead, email account, analytics, or inbox operation. Covers auth, rate limiting, and all commonly used endpoints.
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。
Diagnostic audit for a running cold email program. Checks domain authentication (SPF/DKIM/DMARC), inbox health/reputation from Smartlead, bounce rate by inbox type, and optionally runs a spam placement test via Smartlead's Smart Delivery API. Outputs markdown report + CSV with per-domain/per-inbox scores and concrete action items. Use when reply rates drop, when bounces spike, when onboarding someone else's account, or as a weekly/monthly health check.
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。
Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop".
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。