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概要と使いどころ
60-Second Stock Snapshot — fast assessment with signal (BUY/HOLD/SELL/AVOID), key bullish/bearish factors, and key levels. No subagents. Terminal output only. Triggered by "trade quick <TICKER>" or "quick look at <TICKER>".
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。
Menu engineering analysis — item placement, description quality, pricing psychology, upsell opportunities, photo presence, Kasavana matrix (Stars/Plowhorses/Puzzles/Dogs)
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。
Reads, searches and counts Claude Code session transcripts (the .jsonl files under ~/.claude/projects, subagents too) with the csift command-line tool, and ships hooks that re-inject compacted turns or record pending questions. Use when asked what a past or running session said, did, edited, spent or is doing now; when about to grep, jq or script over a transcript jsonl (a type=="user" filter overcounts the person's messages), count how many messages the person typed, tool calls or tokens, or claim something was never done or decided; to rebuild a lost file or plan from what a session wrote, extract pasted images, restore turns a compaction summary lost, find a subagent's own id when CLAUDE_CODE_SESSION_ID names the parent, wait on or message another session or subagent; or when csift prints "unknown label selector", "show needs an address", "looks like a session/agent id, not a project path" or "0 matches — a DEFINITIVE absence". Not for semantic or embedding search: csift matches regular expressions only.
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。
OpenTSC v2.1: Soul/Shell architecture for interpersonal intelligence. Local, offline-first, with event graphs, judgment engine (K7), self-creation (K8), three-layer attributes, calibrated predictions, 11 VSM professions, and a pluggable zvec memory index (semantic search, identity resolution, jieba segmentation, emotion scoring incl. batched+cached LLM) that runs with zero extra deps. Transforms implicit social judgment into explicit, queryable, auditable, evolving intelligence.
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。
当用户直接要求进行数据集压缩测评，或在量化调优过程中需要使用 AISBench 评测工具输出数据集精度等场景时使用。 本 Skill 负责：使用 AISBench 数据集压缩代码、用 RBF Kernel Herding 算法生成压缩后的数据子集（coreset），并按用户目标交付两种产物之一： ① 接入量化调优主流程：产出独立的 coreset 数据集配置（不覆盖原始数据），回传「全集 config_name + coreset config_name」给编排层，供 evaluation.yaml 切换； ② 仅数据集压缩测评（不做量化调优）：基于 example 模板生成「全集测试脚本」和「子集测试脚本」两份 shell 脚本。 暂时支持 AIME 2025 和 GPQA，其他数据集需要再结合 aisbench tools目录下 herding_coreset_selector 源码进行分析。
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。
Analyze Ascend NPU computation-side profiling data for single-card runs or a selected rank from multi-card runs. Use this skill when the user asks to diagnose computation bottlenecks, AI Core / AI Vector / AICPU hotspots, dynamic shape overhead, block dim issues, redundant TransData/Transpose/Cast, cross-stream waits, frequency/runtime-state issues, or fusion opportunities.
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。
Apply StyleKit visual styles and public assets when building, restyling, or reviewing UI. Use for named StyleKit styles, visual direction, mobile interface patterns, and component-library selection; preserve the target platform and existing product 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。
Schedule social posts to any of 30+ providers via a running postiz instance (hosted at api.postiz.com or self-hosted). Use this skill whenever someone wants to post, schedule, or publish a draft to LinkedIn, Reddit, Bluesky, Mastodon, Threads, Instagram, TikTok, YouTube, Pinterest, Discord, Slack, or any non-Twitter social channel. ALWAYS chain content-atomizer first for platform-specific copy — this skill is a distribution layer only, it does not rewrite copy. For Twitter/X threads, use typefully instead (better thread UX). Triggers: "post to linkedin", "post to reddit", "post to bluesky", "post to mastodon", "post to threads", "schedule via postiz".
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。
End-to-end social content campaign pipeline. Takes a marketing goal and produces scheduled, on-brand social posts with visuals across postiz-supported platforms, while keeping Typefully for X/thread specialist flows and fallback coverage. Chains: CMO strategy, content writing with voice calibration, AI slop audit, selective Paper MCP visual design, and routed scheduling via postiz or Typefully. Each phase has a human gate. Use this skill whenever someone wants to plan and execute a batch of social posts — not just one-off tweets. Triggers include: "social campaign", "schedule posts", "pre-launch content", "content calendar", "social content pipeline", "build up content", "I need social media content for my launch", "help me build social presence", "plan a week of posts", "batch social content", "social media strategy", or any request involving multiple scheduled posts with optional visuals.
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-tier video pipeline: ffmpeg Quick (5s, instant) → ffmpeg Enhanced with Ken Burns (15s, polished) → Remotion Animated (60-90s, production-grade). Takes static slides from Paper MCP or any PNGs and assembles them into platform-ready video. Make sure to use this skill whenever the user has slides, images, or PNGs and wants to turn them into video — even if they just say 'make a video from these', 'animate my slides', 'I have images and need a TikTok', or 'stitch these together'. Also use when they mention ffmpeg video assembly, Remotion-animated slide assembly, Ken Burns effects, or any slides-to-video pipeline. Owns the slides→MP4 assembly pipeline; for writing, debugging, or running `remotion render` on Remotion code itself, see /remotion-best-practices; for screen-recorded product demos, see /marketing-demo. Works with any PNG source — Paper exports, Canva, screenshots, anything.
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 detailed buyer personas and audience profiles from research. Use this skill whenever the user mentions audience, buyer persona, ideal customer, target market, ICP, watering holes, 'who am I selling to', customer research, or audience profile. Also use when content feels unfocused or generic (that's an audience problem), when conversion is low because messaging doesn't resonate, when starting any new project (audience should be first), or when any downstream skill needs audience.md but it doesn't exist yet. Even if the user doesn't explicitly ask for audience research, trigger this if they're writing copy or building a landing page without a clear audience defined. Three approaches: Quick Profile, Persona Build, Community Mining.
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 Apple App Store screenshot pages as a Next.js app with html-to-image export at required resolutions. Screenshots are advertisements, not documentation — every screenshot sells one idea. Use when building App Store screenshots, generating exportable marketing screenshots for iOS apps, or creating programmatic screenshot generators. Triggers on 'app store screenshots', 'App Store', 'screenshot generator', 'iOS screenshots', 'marketing screenshots', 'phone mockup', 'ASO screenshots', 'app store assets', 'app listing', 'app store page', or 'app preview images'. Also use when someone is about to submit an app and needs store assets, or when they say 'make my app store page look good'. Includes iPhone and iPad mockup components with pre-measured dimensions.
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。
Write copy that converts. Use when writing landing pages, emails, sales copy, headlines, CTAs, social posts, cold emails, or any persuasive text. Triggers on 'copy', 'copywriting', 'sales copy', 'landing page copy', 'cold email', 'headlines', 'write me a page', 'make this convert', 'rewrite this copy', or any request involving persuasive writing. Three modes: Generate (write from scratch), Edit (improve existing copy with Seven Sweeps), Cold Email (outbound sequences). If someone has text that needs to sell harder, this is the skill.
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 enriched ICP-based lead lists with Exa Agent, including structured scoring and CSV output. Use when generating leads, building prospect lists, finding companies to sell to, outbound research, or ICP-based company discovery. Triggers on leads, lead gen, prospect list, find companies, ICP, outbound list. Distinct from lead-magnet (content asset that captures emails).
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 complete narrated MYTHIC SHORT FILM end-to-end on Unsora MCP in the layered cut-paper diorama style — stacked matte cardstock worlds, a strict three-colour palette, exposure that swings, paper wipes hiding every seam, landing on a face. Animation-movie storytelling, not an explainer: gods, monsters, heroes, folklore, origin myths and transformations, told in ten-second story beats with a mythic narrator, native paper foley, and one assembled MP4. Use whenever the user wants a myth, legend, fable, folktale or fairy-tale short, a cut-paper or papercraft animated story, "tell the story of X" as a video, a stop-motion-look mythic film, or says "run the cardstock diorama myth animation" or "run the diorama myth pipeline" — even with no story given, since the skill proposes myths itself. NOT for fact-driven explainers with charts and statistics (that is vox-motion-graphics).
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。
Built by DynG AI for PlatformPilot.ai-style Go agent runtimes. Use when the user wants to scaffold HandoffKit runtime primitives into a Go project: channel-backed mailboxes, select, router, broker, join/quorum barriers, trace, budget, corpus/compactor, supervisor/nursery, dead letters, and sketch interfaces. Trigger words include PlatformPilot scaffold, scaffold handoffkit, add the HandoffKit runtime, set up message-passing agents, or drop in CSP agent primitives.
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。
Built by DynG AI for PlatformPilot.ai-style multi-agent systems. Use when designing or reasoning about message-passing agent coordination in ANY language: actor-style mailboxes, select, point-to-point routing, pub/sub, fan-in joins/quorums, ownership handoff, budgets, dead letters, and traces. Trigger words include PlatformPilot, DynG AI, actor model agents, message-passing agents, CSP agents, coordinate agents, multi-agent orchestration, agent runtime, fan-out workers, pub/sub agents, agent barrier, or join.
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。
RED-GREEN-MUTATE-KILL MUTANTS-REFACTOR workflow for writing production code. Use before ANY production code change - new features, bug fixes, or behavior changes. Triggers on starting implementation work of any kind. Covers the cycle itself - failing test first, minimum code to pass, mutation verification, refactor assessment. For how to write good tests, see testing. For the refactoring step in detail, see refactoring. TDD is non-negotiable.
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 or reorganize .NET solutions with clean project boundaries, repeatable SDK settings, and a maintainable baseline for libraries, apps, tests, CI, and local development.
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Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"
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 developing in packages/agent-core-v2 (the DI × Scope agent engine) — adding or modifying a domain Service, choosing a LifecycleScope, wiring DI dependencies, splitting a domain across scopes, owning or migrating a config section, gating behavior behind an experimental flag, raising coded errors, working on the permission system, writing DI/Scope tests, porting business logic from agent-core (v1) to v2, triaging a main-branch commit against v2, or exposing a v2 domain over server-v2 while keeping the /api/v1 wire contract compatible with released clients. Self-contained guide organized by development stage (orient → design → implement → test → verify) plus align workflows for v1→v2 migration, main-branch commit triage, and server-v2 wire exposure; each file carries the rules, examples, and red lines for its step.
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 modifying the pythinker-code terminal UI in apps/pythinker-code/src/tui — components, dialogs/selectors, slash commands, themes, streaming render, or the PythinkerTUI controllers. Covers the architecture, where new features go, test placement, the theme system mechanics, and the dialog interaction/visual spec (DESIGN.md).
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。
Evaluate a local skill with the terum-skills CLI — hygiene, trigger evals and execution cases against a baseline, billed to the user's own Claude Code — after confirming the cost, and show the result as a Markdown board. Use when the user asks to eval, test, score or benchmark a skill, or to see whether an edit made it better.
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。
Do a task end-to-end — implement, PR, CI loop, ship. ONLY invoke when the user explicitly types `/do` or `$do`; never auto-select from a natural-language request, even one that sounds like an end-to-end task.
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。