「pth」の検索結果

Martial arts as body discipline — the shared pedagogical structure across striking, grappling, and weapon arts (stance, distance, timing, ukemi, live partner work, graded ranking, and the ethical container the best schools enforce). Covers karate, judo, jiu-jitsu (Brazilian and traditional Japanese), aikido, kendo/kenjutsu, boxing, muay Thai, and wrestling at enough depth that an agent can place a user into a reasonable first-month practice and recognize the safety failures that matter most. Leans on Moshé Feldenkrais's judo background and Yang Jwing-Ming's martial scholarship for the internal-to-external bridge. Use for any query about beginning a martial art, training injury patterns, graded progression, or the ethics of combat training.

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。

Understanding how digital systems actually work -- hardware, operating systems, networks, and information representation -- at a depth sufficient to reason about them rather than just use them. Covers CPU/RAM/storage/GPU roles, what an OS does, how packets travel the internet, and how computers represent numbers, text, images, and sound as binary. Use when a learner needs to build a mental model of computing rather than memorize menu paths.

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。

Observational drawing and visual perception techniques for art education. Covers contour drawing, gesture drawing, negative space, proportion and measurement, value mapping, spatial depth cues, and the cognitive shift from symbolic to perceptual seeing. Use when teaching drawing fundamentals, analyzing observational accuracy, or developing visual literacy in any medium.

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。

Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.

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。

Real-time quotes, K-line charts, order book, trade ticks, intraday capital flow, market sentiment temperature, trading session schedule, security lists, exchange rates, and IPO calendar for HK/US/A-share/SG via Longbridge. Also covers ADR premium and FX carry frameworks. Triggers: "股价", "行情", "K线", "走势", "盘口", "资金流", "市场温度", "汇率", "IPO", "打新", "隔夜股", "ADR溢价", "外汇套息", "K線", "盤口", "資金流", "市場溫度", "匯率", "ADR溢價", "外匯套息", "现在多少钱", "多少钱", "stock price", "quote", "kline", "chart", "depth", "orderbook", "capital flow", "market sentiment", "exchange rate", "IPO calendar", "security list", "ADR premium", "fx carry", "market open", "trading hours", "开市", "溢价", "NVDA.US", "700.HK", "600519.SH", "股價", "走勢", "開盤", "今天開市"

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。

Zip recorded Anabasis v2 runs for handover at a chosen depth (--light, --medium, --verbose). Use when the operator asks to zip, bundle, archive or send a run, a round, its log, its harness or "everything the model saw", or names a size cap. One command, three cumulative levels, any number of runs, a README, a reading guide and a MANIFEST inside every zip.

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。

Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.

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 whenever creating, renaming, or editing any file under docs/ in this repo, or when asked to compile/build the book PDF. Enforces the exact .mdx frontmatter, ID scheme, and heading-depth rules required by the go-pretty-pdf tool (https://github.com/sazardev/go-pretty-pdf) so the whole book keeps compiling.

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。

Icarus Figures produces publication-grade figures for scientific papers — reproducible matplotlib/seaborn data figures and original TikZ method/framework/architecture figures, held to a four-axis quality bar (depth · elegance · unimpeachable · visible-gap) and exported as editable PDF+PNG+SVG with a runnable critique gate. Use this whenever a figure is destined for a paper, journal, conference submission, thesis, or report — making a plot/chart publication- or journal-ready, building a method/architecture/framework diagram or 技术路线图 (the hero figure a paper opens with), a schematic or workflow figure, or cleaning up a matplotlib/seaborn/TikZ figure that currently looks like a homework plot. Trigger even when the user never says "publication": if the figure goes into a written scientific document, this skill applies.

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。

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.

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.

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。

Systematically challenge current assumptions before major decisions. Counters confirmation bias, groupthink, and overconfidence.

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-based complexity assessment for task analysis. Use when determining the appropriate workflow, phases, and validation depth for a 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。

Deeply analyzes Agent Studio framework structural health: catching phantom require() references, wrong module depth paths, missing skill/agent dependencies, bloated configurations, archived references in active code, stale catalog counts, and empty tool/skill directories.

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。

Devil's Advocate stress-testing for code, architecture, PRs, and decisions. Surfaces hidden flaws through structured adversarial analysis with metacognitive depth. Use for high-stakes review, stress-testing choices, or when the user wants problems found deliberately. NOT for routine code review. Triggers on "스트레스 테스트", "stress test", "devil's advocate", "반론", "이거 괜찮아", "문제 없을까", "깊은 리뷰", "critical review", "adversarial".

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 physically-based atmospheric scattering shaders — sky domes, planetary atmospheres, LUT-optimized pipelines, depth-aware post-processing. Four modes — sky-dome, atmosphere-post, planet, lut. Triggers on atmospheric scattering, sky shader, sunset rendering, planet atmosphere, Rayleigh scattering, Mie scattering, volumetric sky, sky dome, atmosphere post-processing, aerial perspective, transmittance LUT, sky rendering, realistic sky, planetary rendering.

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 distinctive, production-grade frontend interfaces — websites, landing pages, dashboards, React components, HTML/CSS layouts, editorial heroes with depth-parallax (Astryx pattern), pointer-reactive fluid effects, pixel-glitch canvas heroes and terminal-style tool-panel dioramas (Composio pattern). Avoids generic AI aesthetics. Triggers on web UI, styling, beautify, frontend design, dashboard, landing page, React component, editorial hero, glitch hero, dev-tool landing page.

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。

Recreate grainient.supply's 16 dark-mode visual effects as single-file HTML pages: WebGL shader gradients, vignette overlays, 9-layer box shadows, smooth scroll, spring animations, hover-zoom, ticker marquees, glassmorphism, 3D card flips, bento grids, gradient CTAs. Dark-mode-first with lime green (#C2F13C) accent. Triggers on grainient effects, dark-mode landing page, cinematic depth, glow effects, SaaS showcase, visual effects page.

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。

Deep, iterative, multi-source research that explores a topic from multiple perspectives, detects contradictions, and produces a comprehensive vault note with fact-level citations and a confidence map. Use this skill whenever the user says /deep-research, "deep research X", "research X thoroughly", "investigate X deeply", "I need to really understand X", or wants research that goes beyond a quick web search. Also use when the user wants to understand a complex, contested, or multi-faceted topic, compare competing approaches with evidence, or build a comprehensive mental model they can trust for decisions. This is heavier than /research — it searches web, academic papers, Reddit, and the vault, then loops through exploration and critique rounds until the evidence base is solid. When in doubt between /research and /deep-research, prefer this one if the topic is complex, contested, or the user wants depth over speed.

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。

Guides selection of identity, reasoning, and output approaches for Claude prompts based on task characteristics. Trigger on: "help me choose an approach," "which approach fits this task," "recommend a prompt pattern," "compare reasoning methods," "map this task to the right approach," "what combination of approaches," "which identity fits," "which reasoning method." Also trigger on symptom-phrased: "my prompt feels generic," "I don't know which approach to use," "my output lacks domain depth." Covers decision-tree logic across 8 identity approaches, 18 reasoning variants, and 10 output formats. After selection, use the relevant catalog skill if available to retrieve full templates. Activate whenever approach-selection across multiple categories is the primary decision. Do NOT use when the user already names a specific approach to retrieve (use the relevant catalog skill directly if available) or for evaluating existing prompts (use rootnode-prompt-validation if available).

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。

Conversational profile builder. Produces validated JSON config files for any rootnode Skill that consumes profile-shaped configuration (handoff trigger check, mode router, critic gate, future Skills). Reads a target JSON Schema (draft-07), conducts a progressive-depth interview using plain-language questions, validates answers, and writes the resulting JSON to a destination path. Schema-agnostic — works with any profile schema conforming to draft-07. Use when a user needs to create, clone, or revise a profile and you do not want them hand-editing JSON. Trigger on: "build me a profile," "create a profile," "I need a profile for X," "set up my profile," "edit my profile," "clone the X profile," "walk me through making a profile." Do NOT use when the user already has a working profile and only wants to invoke the consuming Skill, when the schema cannot be located, or for non-profile JSON config work. Always validate before writing.

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。

Audits and scores Claude Projects using a six-dimension Scorecard with anchored 1-5 rubrics and detects seven structural anti-patterns. When global layer info is provided, adds cross-layer alignment findings. Use when user says "audit my project," "review my custom instructions," "score my project," "evaluate my Claude project," "improve my system prompt," "what's wrong with my project," "why is my project underperforming." Also trigger on symptom-phrased: "my project doesn't work right," "Claude is inconsistent in my project," "my Project used to work and now doesn't." Also use when the user pastes Custom Instructions asking why output is poor or generic. Do NOT use when the user's primary request is a global-layer audit (use rootnode-global-audit if available), single-prompt evaluation (use rootnode-prompt-validation if available), or Memory-only optimization (use rootnode-memory-optimization if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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。

Builds complete, optimized Claude prompts and Project scaffolds from task descriptions. Use when building, designing, creating, or structuring a Claude prompt or system prompt. Trigger on: "build me a prompt," "compile a prompt for," "create a system prompt," "write a Claude prompt," "design a prompt for," "help me write a prompt," "scaffold a Claude Project," "design a Project for." Uses a four-stage methodology (Parse, Select, Construct, Validate) and a tested 5-layer architecture (Identity, Objective, Context, Reasoning, Output + Quality Control). In Project Mode, the Compiler is global-layer-aware — checks User Preferences, installed Skills, and MCP Connectors to avoid redundancy and flag gaps. Do NOT use for auditing existing prompts (use rootnode-prompt-validation if available) or diagnosing existing Projects (use rootnode-project-audit if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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。