582건 · 관련도순
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.
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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.
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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"
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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.
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Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.
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Research a topic in depth for the current or given task plan, by combining Internet/Web search with a grounding in the source artifacts of the project, and append the resulting research report to the "research" attachment of the task, optionally refining the plan by its recommendations. Use when the user wants to "research", "investigate", or "look into" a topic for a "task" or "plan".
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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.
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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.
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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 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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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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Plan synthetic routes and judge whether a proposed molecule can actually be made, using AiZynthFinder's Monte-Carlo tree search over template-derived reactions and a purchasable building-block stock. Use this skill to configure expansion and filter policies, choose a stock file, run route search over a candidate set, and read the returned trees — solved fraction, route depth, and which building blocks a route bottoms out in. Also trigger on AiZynthFinder, retrosynthetic tree search, synthetic accessibility, SAscore, RAscore, building-block stock, reaction template, or route scoring.
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Use this skill when a company needs to decide how much assessment each supplier deserves, or asks "tier our vendors", "which suppliers are critical", "we have 200 vendors and cannot assess them all", "build a third-party risk tiering", "rank suppliers by risk" or "which vendors need a security review this year". Builds the complete supplier population from finance, single sign-on and contracts, scores each supplier on data, access and dependency, assigns a tier by the highest axis, sets the assessment depth and cycle per tier, and writes a tiered list with the reason for every score.
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Flatten nested conditionals with early returns or table-driven methods - keep nesting depth under 3 levels
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Validate at every layer data passes through to make bugs impossible
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Implement layered collective defense using alarm signaling, role mobilization, and proportional response. Covers threat detection, alert propagation, immune response patterns, escalation tiers, and post-incident recovery for distributed systems and organizations. Use when designing defense-in-depth where no single guardian covers all threats, building incident response that scales with severity, or when current defense is over-reactive to every alert or under-reactive to genuine threats.
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AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.
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Master skill composing the 5-step synoptic cycle for panoramic synthesis across multiple domains. Orchestrates meditate, expand-awareness, observe, awareness, integrate-gestalt, and express-insight into a coherent process that produces unified understanding rather than sequential compromise. Use when a problem genuinely spans 3+ domains and the interactions between domains matter more than depth in any one, when sequential analysis feels like compromise rather than integration, or before major architectural decisions affecting multiple stakeholders.
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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.
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AI-based complexity assessment for task analysis. Use when determining the appropriate workflow, phases, and validation depth for a task.
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This skill should be used when the user asks to "make an isometric animation", "build a 2.5D isometric scene", "create an isometric infographic", "animate an exploded diagram", "do an isometric city/stack build", "show stacked layers in iso", "extrude blocks with depth", or "add a gentle camera drift to an iso scene". Covers CSS 3D transforms, SVG iso planes, and Three.js OrthographicCamera for true 3D iso — no build step.
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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.
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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".
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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.
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