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概要と使いどころ
Structured exposure habits for building taste through relentless, intentional consumption. Not passive scrolling. Active intake across design, architecture, film, music, food, and culture. Use when building a taste practice, advising on professional development, or diagnosing why someone's design range feels narrow.
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 brands and products across social media — share of voice, sentiment, positioning, and audience overlap using Xpoz. Use when asked to "compare brands", "competitive analysis", "share of voice", "brand vs brand", or "competitive 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。
Analyze brand or topic sentiment across Twitter, Reddit, and Instagram using Xpoz. Classifies posts as positive/neutral/negative, extracts recurring themes, and generates a sentiment report. Use when asked for "sentiment analysis", "what are people saying about X", "brand sentiment", or "social media opinion on X".
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。
Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.
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 parallel coding agents across repositories through the AO daemon. Generated from plugin-commands.json; invoke as $bdb-aos:orchestrator.
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。
Release tdmcp: write the Keep-a-Changelog entry, bump the SemVer version across every manifest, then (autonomously, per project policy) commit, tag, and push — gated on a td-qa PASS, with hard git safety rails. Use when releasing/shipping/cutting a tdmcp version, writing the CHANGELOG, bumping the version, or tagging a release.
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。
How to migrate the tdmcp Codex Desktop bundle from legacy .dxt to .mcpb (MCP Bundle) and keep it building — covers the manifest schema (verify against the installed packer, never hardcode), the build-dxt.mjs packer/zip-fallback flow, the npm scripts, and the full .dxt→.mcpb reference sweep across docs and scripts. Use when packaging or migrating the tdmcp desktop bundle.
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。
Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline 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。
Build a show across lights (grandMA3), media (Resolume) and generative visuals (TouchDesigner) from one cue list, offline first. A lane whose console or app is not running is skipped and logged while the others continue; the live rig is touched only after GO. Use for "build the show", "cue list to grandMA3 Resolume and TouchDesigner", "show programming".
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。
Clean up git worktrees across your repos: list every worktree, classify it as merged, remote-only, local-only or dirty, recap what each holds, and remove only the merged clean ones after GO. Use for "clean up worktrees", "what is in my aos-wt folders", "land my worktrees", "prune worktrees".
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 a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO. Use as the umbrella skill when the user asks for a full SEO analysis or strategy.
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。
Audit technical SEO across crawlability, indexability, security, URLs, mobile, Core Web Vitals, structured data, JavaScript rendering, and related platform signals like robots.txt and AI crawler access.
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。
Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
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 in strict POSIX sh scripting for maximum portability across Unix-like systems. Specializes in shell scripts that run on any POSIX-compliant shell (dash, ash, sh, bash --posix).
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 efficient, scalable monorepos that enable code sharing, consistent tooling, and atomic changes across multiple packages and applications.
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。
BDB local-first long-term memory engine (memB). Use when querying, remembering, or adapting preferences, code architectures, and developer patterns across tasks.
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。
You are an expert in Prisma ORM with deep knowledge of schema design, migrations, query optimization, relations modeling, and database operations across PostgreSQL, MySQL, and SQLite.
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 workflow for summarizing work that still needs human judgment across configured pull requests, issues, feedback, errors, and delivery signals. Use for a human decision queue or bounded 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。
Use when acting as the multi-project orchestrator and lead coordinator across repositories using the Agent Orchestrator (AO) daemon. Spawns, inspects, coordinates, and reviews parallel coding agents in isolated Git worktrees.
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-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your 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。
Use when a task needs a small, throwaway multi-agent fan-out (a couple of parallel workers plus a review pass) in ANY project — trigger phrases "spawn a few parallel agents", "fan out", "quick worker team" — without the full /startcycle-graph contract, no .agents/graph.md bootstrap, no state.json schema, no persistent files. Roles run on the session model unless `.aos/pipeline.json` overrides one (an external CLI can take the worker step) and portable across machines that may not have Antigravity/OpenCode/Codex 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。
Interactive 9-step prompt crafting and delegation protocol for autonomous multi-agent teams. Enforces objective verification, integrity modes, and acceptance criteria across Antigravity, Claude Code, Cursor, OpenCode, Codex, and Roo 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。
Feishu (Lark) unified CLI for tasks, documents, wiki, bitable, messaging, approval, and Drive. Supports search/create/edit/publish/export across all modules. Use when reading/writing Feishu docs, searching docs or wiki, managing tasks, sending messages, creating approvals, exporting to Markdown, or any 飞书/Lark interaction.
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 the `rimo` CLI to interact with the Rimo platform — list/read/search meeting notes, transcripts, and documents, ask AI questions across them, and create notes or append markdown sections to them. Trigger when the user mentions Rimo, asks about meeting notes/minutes/transcripts/documents stored in Rimo, or invokes `rimo` directly.
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。