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概要と使いどころ
Orchestrator that routes a UI/UX task through brand, tokens, layout, components, polish and accessibility. Use for multi-concern work such as a design review, UI build or interface audit.
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Find opportunities to improve web application code using TanStack libraries (Query, Table, Form, Router, etc.). Avoid man-with-hammer syndrome by applying TanStack after vanilla implementation works.
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Carbon allotropes and nanoscale materials — graphite, diamond, fullerenes (C60 and family), carbon nanotubes, graphene, and the broader class of low-dimensional materials. Covers synthesis routes (arc discharge, laser ablation, CVD, exfoliation), structural characterization, exceptional mechanical and electronic properties, and the gap between laboratory demonstrations and structural-scale applications.
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Networking fundamentals as they apply to cloud infrastructure — virtual networks, subnets, routers, NAT, floating IPs, security groups, VLAN/VXLAN segmentation, load balancing, SDN concepts, and how Neutron-style cloud networks sit on top of physical topology. Covers TCP behavior at scale, congestion control, tail latency, overlay networks, and the operational gotchas that come from network layering. Use when designing cloud network topology, debugging cross-AZ latency, or reviewing a proposed VPC/SG design.
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Use the moment a request is underspecified and you are about to act on an ASSUMED goal. Enumerate the candidate goals the request could mean, project the action or artifact each one implies, and check whether they diverge: if two or more plausible goals lead to materially different actions or artifacts, ask exactly ONE targeted clarifying question; otherwise proceed on the most-likely goal and state the assumption in one line. Clarification is an evidence-producing action, not a delay — but one question, never an interrogation. Distinct from gsd-spec-phase (GSD-phase-bound, emits a heavy SPEC.md) and intent-router (fetch strategy, not goal disambiguation). Backed by agent goal-state inference (arxiv 2606.16813v1). Triggers on acting under an assumed goal when the request admits more than one materially different reading.
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Run this appropriateness check the moment you are about to integrate a retrieved long-term memory — a Grove content-addressed hit, a chroma/pgvector neighbour, a memory-consolidation digest, or a MEMORY.md line — into a response, especially anything touching private origins, Fox Companies IP, credentials, or Center Camp / consent-governed content. It answers a question intent-router never asks: not WHAT to fetch or HOW, but WHETHER a correctly-retrieved item should reach output. Relevance is not appropriateness — a perfect similarity match can still be a boundary violation. Default is FAIL-CLOSED: if in-context authorization is uncertain, the memory may inform behaviour but must not be surfaced. Backed by RBI-Eval (arxiv 2606.06055v1). Triggers on surfacing recalled sensitive memory into a response.
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Use when the user asks "what should I work on", mentions GSD phases, ROADMAP, or .planning/ artifacts. Routes to the correct GSD command for the current project state.
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Electronics Educational Pack — routes queries to 15 modules covering Ohm's law through PCB design
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Meta-mathematical connections, cross-domain synthesis, and the Complex Plane as a navigational tool. Classifies problems by quadrant (Abstract/Embodied x Logic/Creativity), routes them to relevant domains, and traces dependency chains. Use when classifying mathematical problems across domains, navigating the Complex Plane of Experience, finding cross-domain connections, or building multi-domain solution strategies.
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Zephyr RTOS development — boards and devicetree, the build system (west, Kconfig, CMake, sysbuild), drivers and peripherals, BLE and networking, the kernel, storage, power, testing and debugging, security and OTA. Use this for ANY Zephyr RTOS or embedded-firmware task on a Zephyr project; it routes you to the right specialized skill via the zephyr-cli registry.
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Set up and maintain Hierarchical Agent Memory (HAM) for Codex using scoped local memory files. Trigger on "go ham", "set up HAM", "ham commands", "ham help", "ham route", "ham remove", "ham update", "ham status", "ham benchmark", "ham baseline start", "ham baseline stop", "ham metrics clear", "HAM savings", "HAM stats", "HAM dashboard", "HAM sandwich", "HAM insights", "HAM carbon", or "HAM 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。
Set up Hierarchical Agent Memory (HAM) — scoped CLAUDE.md files per directory that reduce token spend. Trigger on "go ham", "set up HAM", "ham commands", "ham help", "ham route", "ham remove", "ham update", "ham status", "ham benchmark", "ham baseline start", "ham baseline stop", "ham metrics clear", "HAM savings", "HAM stats", "HAM dashboard", "HAM sandwich", "HAM insights", "HAM carbon", or "ham sync".
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 claiming the AI bounty on the tDVV mainnet sidechain. This public claim skill now supports Portkey AA/CA only, requires CA sync and holder preflight before any write, and routes to AA/CA onboarding, AA/CA claim, or diagnostics-only stop handling.
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Google Calendar management via CalendarACSet. Transforms scheduling operations into GF(3)-typed Interactions, routes to triadic queues, detects saturation for balanced-calendar-as-condensed-state.
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Interleave layer bridging the BigQuery cluster to plurigrid/asi. Routes BigQuery queries through asi's DuckDB stack, wires patent search into asi knowledge graph, connects Looker Studio dashboards to CatColab, and feeds BigQuery ML into the lolita physics emulation pipeline.
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This skill should be used when the user asks to "brainstorm", "explore options", "get creative", "what if we...", or selects "Let's get creative" during story or cycle creation. NOT for a bare vague feature idea where generating options would mean inventing the premise first - that routes to /craft:riff (riff first, options after). Generates 3-4 creative options with trade-offs, visual direction for UI stories, and wireframes.
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Enforcement layer for chunk and story validation. Invokes the chunk-validator agent (haiku), enforces the verdict, routes failures to refine-chunk or test-fix, captures CLI learnings. The orchestrator invokes this skill — never the agent directly.
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Use when the user explicitly asks Rewrite Room to route documentation work, or when audit/sync/freshness, user-facing authoring, citation-driven writing, docs-to-skill conversion, and AI-instruction optimization overlap and exactly one workflow must be chosen.
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Route requests to summarize files, URLs, images, inline text, or multiple sources. Select the requested format and preserve evidence, exact counts, uncertainty and source coverage through summarization, synthesis and agent-result relay.
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Use when working with Python tooling — uv package management, Hatchling build backend, ty or mypy type checker configuration, ruff linting, pre-commit hook setup, TOML read-write with tomlkit or tomllib, or PyPI packaging and release workflows. Routes to standalone specialist skills for deep dives on any single tool.
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。
Routes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only scripting.
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。
Activates on any Python task involving *.py files, uv, ruff, ty, pytest, or pyproject.toml — loads the shared Python 3.11+ standards and routes the task to the specialist skill that applies them: TDD, CLI, web, data, async, typing, packaging, publishing, documentation sites, test design, test-failure analysis, or stdlib-only constrained environments.
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。
Python web and API development enforcing strict route/domain/data layer separation, Pydantic v2 strict request-response models, edge-resolved auth, and async-safe HTTP clients. Use when working with FastAPI, Starlette, Django, Flask, HTTP endpoints, request models, authentication flows, async handlers, or any Python web framework 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。
Provides agent selection criteria, workflow patterns (TDD, feature addition, code review, refactoring, debugging), quality gates, and python-cli-architect vs stdlib-scripting routing for Python engineering tasks. Activated by python-engineering:orchestrate at Step 1 before any task is routed. Also activates when an orchestrator needs to select the correct Python specialist agent or chain agents across a multi-step Python 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。