1.3万 件 ・ 関連度順
概要と使いどころ
15-minute daily taste exercises. Monday through Friday. Compound effect over time. Use when building personal practice habits, training a team's design eye, or adding structure to professional development.
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Response timing, acknowledgment, and making the interface feel alive. Every action deserves a response at the right speed. Use when designing interactions, evaluating responsiveness, or diagnosing why a product feels sluggish or dead.
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Build taste through volume of output, deliberate failure, and speed. Taste cannot be developed by watching. It's sharpened by making, failing, and making again. Use when designing practice routines, breaking through creative blocks, or helping someone move from analysis to execution.
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GitHub Actions CI/CD setup for Python, R, and multi-platform testing. Use when creating, debugging, or optimizing CI/CD pipelines.
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Develops an implementation plan ready for wave-orchestration to execute. Takes the user's goal or rough plan as input, mines the codebase for facts, grills the user one question at a time for the decisions, drafts the planning/ artifacts (task DAG, wave table, worker prompt template, state file), then reviews its own plan on two axes before seeking approval. Use when the user wants to turn a feature idea, master plan, or backlog into a wave-orchestration execution plan.
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Alternative Slowbar coffee intelligence — scientific analysis from seed to cup using First Principle + System Thinking. Covers: varieties, terroir, cultivation, disease diagnosis, processing, roasting physics/chemistry, extraction science, brewing, business strategy, storytelling. ALWAYS trigger for coffee-related questions requiring scientific depth. DO NOT trigger for simple recipes or general food questions. Style: science-driven, farmer-first, quality-obsessed.
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Authoritative reference for submitting tdmcp to the Anthropic Connectors Directory as a Codex Desktop Extension (MCPB). Use whenever drafting, checking, or fixing the submission — it defines the two submission paths, why tdmcp is a Desktop Extension (never a remote connector), every form field, the rejection-causing gates, and the local-only compliance story. Read this before writing any submission deliverable.
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Run a prompt repeatedly on an interval, using the harness built-in plus loop templates. Generated from plugin-commands.json; invoke as $bdb-aos: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。
Build a tdmcp TouchDesigner-bridge vertical slice the house way — promote an op from /api/exec to a first-class REST endpoint (e.g. POST /api/connect, GET /api/logs, node_detail flags), add its typed method in src/td-client/touchDesignerClient.ts, its Zod envelope in src/td-client/validators.ts, rewire the tool(s) to prefer the endpoint with an exec fallback, and write py_compile + td/tests unittest + offline msw client tests. Use when adding/changing a bridge REST endpoint, editing td/, extending node_detail/get_bridge_logs, promoting connect/disconnect/param-modes/DAT-text off exec, or doing any exec→REST work — especially the td-depth bridge-robustness backlog. Honors probe-live discipline when TouchDesigner is offline.
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Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.
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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.
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Consolidate the five tdmcp surveyor reports into one prioritized FEATURE_BACKLOG.md — dedupe cross-surface overlaps, reconcile every candidate against the roadmap (NEW vs planned vs extension), rank by a selectable impact×effort weighting profile into P0/P1/P2 (high-confidence first), and emit per-surface tables + a recommended-next shortlist that hands straight to the build pipeline. Use when a td-synthesizer agent is consolidating surveys during the feature-discovery harness.
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Bring a new machine to a verified AOS installation: read-only doctor baseline, install after GO, MCP servers wired per harness with the configs backed up first, memB and OpenWiki checks, and a second doctor run for the delta. Use for "set up this machine", "onboard a new computer", "install AOS on this laptop".
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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".
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Split one big task into chunks of at most 25 minutes, each with a done-check, and place the demanding ones in your high-energy hours. Use for "split this task", "break it into chunks", "I can't start this", "focus plan". Nothing leaves your computer.
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Comprehensive guide to auditing web content against WCAG 2.2 guidelines with actionable remediation strategies.
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Use when adding interactive 3D scenes from Spline.design to web projects, including React embedding and runtime control API.
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Configure Turborepo for efficient monorepo builds with local and remote caching. Use when setting up Turborepo, optimizing build pipelines, or implementing distributed caching.
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Create 3D scenes, interactive experiences, and visual effects using Three.js. Use when user requests 3D graphics, WebGL experiences, 3D visualizations, animations, or interactive 3D elements.
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, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.
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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.
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Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.
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Use when a task should repeat on a schedule or until a condition holds (CI until green, follow a PR to merge, review rounds until no blockers, daily session summary). Ships ready prompt templates with run and duration limits, stop conditions and go-gate safety rules, and per-harness loop invocation.
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。
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
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。