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cccskills

「foundations」の検索結果

127 件 ・ 関連度順

概要と使いどころ

Theory of Constraints primitives for focusing steps, drum-buffer-rope, throughput accounting, critical chain, and policy constraints. Use when sequencing by bottleneck.

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。

vasilyu1983/AI-Agents-public952026年10月12日 更新

muse

無料

Defining and managing design tokens, applying token systems to existing codebases, building design system foundations. Use for spacing, color, typography, dark mode, cross-platform output.

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。

simota/agent-skills922026年10月12日 更新

Compatibility alias for existing OpenClaw installations that now applies Carapace semantic tokens, themes, shared CSS foundations, consumer adapters, and established local primitives.

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。

openclaw/docs762026年10月13日 更新

Build or modify OpenClaw application UI using canonical semantic tokens, themes, shared CSS foundations, consumer adapters, and established local primitives. Use for product interfaces, component styling, theme work, or design-token integration.

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。

openclaw/docs762026年10月13日 更新

Use when asked to create a brand identity, define visual design direction, generate a color palette or type system, build a style guide, or establish the look and feel for a product. Examples: "create a brand for X", "define the visual identity", "what colors should we use", "build a style guide", "design system foundations".

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。

tonone-ai/tonone762026年10月5日 更新

Foundational concepts in nutrition science — macronutrients, micronutrients, energy balance, Atwater factors, reference intakes (DRI/RDA/AI/UL), food composition tables, and the methods of human nutrition research. Grounds the rest of the department in a shared vocabulary and in the measurement limits of the field, including controlled-trial history, observational-study limits, and the biochemical basis for calorie accounting. Use when a question asks what something "is" nutritionally, how energy and nutrients are measured, or what the reference numbers mean.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

The logic of sentential connectives -- and, or, not, if-then, if-and-only-if -- as a formal system. Covers syntax (well-formed formulas), semantics (truth tables), satisfiability, validity, logical equivalence, normal forms (CNF, DNF), natural-deduction rules, and common translation pitfalls. Use when formalizing arguments with propositional structure, checking validity mechanically, or teaching the foundations of formal reasoning.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Foundations of individual economic decision-making, market structures, and strategic interaction. Covers supply and demand analysis, price elasticity, consumer and producer surplus, market structures (perfect competition, monopoly, oligopoly, monopolistic competition), game theory (Nash equilibrium, dominant strategies, repeated games), and welfare economics. Use when analyzing individual markets, firm behavior, pricing strategies, consumer choice, or strategic interactions between economic agents.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Foundations of digital signal processing — sampling, aliasing, the Nyquist criterion, quantization, convolution, the discrete Fourier transform, FFT, FIR and IIR filter design, windowing, spectral leakage, and practical issues in fixed-point versus floating-point implementation. Use when designing filters, analyzing spectra, choosing sample rates, reasoning about aliasing, or implementing DSP algorithms on a microcontroller, DSP chip, or host CPU.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning pipeline.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Pure mathematical structure. Sets, groups, rings, fields, topology — the formal bedrock everything else rests on.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Foundational skills for Zephyr RTOS development. Covers essential Embedded C patterns (BIT, CONTAINER_OF), real-time concurrency primitives (mutexes, semaphores, spinlocks), hardware literacy (datasheet-to-DTS mapping), and defensive programming. Trigger when writing core application logic, drivers, or troubleshooting foundational behavior.

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。

beriberikix/zephyr-agent-skills692026年5月19日 更新

design

無料

Use when a non-designer needs to audit a UI, generate a design spec (spacing, type scale, color tokens, grids), or build brand foundations (logo systems, palette and type pairing, brand guidelines). Covers the visual layer, UX/perceptual critique, and brand identity. For implementing the design in code (React/HTML/CSS), use frontend-design.

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。

firatcand/founder-skills382026年7月2日 更新

Audits brand/ files for completeness, consistency, and freshness. Use when the agent or user wants to review brand files, audit marketing docs, check brand consistency, verify brand health, or assess what's missing from brand memory. Produces a structured audit report with per-file scores, cross-file contradiction detection, staleness flags, and recommended next skills to run. This is the quality gate for the brand memory system. Also use when someone says 'check my brand', 'brand audit', 'what's missing', 'is my brand ready', 'brand health', 'review my marketing docs', or before running any campaign to verify brand foundations are solid.

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。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

Use when a task spans multiple steps, files, or unknowns — before planning the order of work, whenever about to report completion or success in any wording, and when picking the next action after a result, failure, or surprise. Also under deadline pressure, or when resuming work built on questionable foundations.

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。

wsbm393/Fable-Skill262026年7月12日 更新

Build and audit PFC2D/PFC3D 5.0 model foundations for asphalt cases, including lifecycle, domain, balls, walls, clumps, groups, ranges, top-level cmat, staged saves, and source-version purity.

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。

Echo-aloha/asphalt-codex-skills-5262026年8月26日 更新

Expands one indicator into the full scope of an incident: pivoting across data sources to find related hosts, accounts, and infrastructure, building a timeline, and bounding what is and is not affected. Activates for requests to scope an incident, pivot from a single IOC, or determine the blast radius of a detection.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Identifies a sample's true file type independent of its extension: matching magic bytes and structural signatures, detecting container/archive formats, and flagging extension-content mismatches used to disguise malware. Activates for requests to identify a file type, check magic bytes, or detect a disguised/spoofed extension.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Computes cryptographic and fuzzy fingerprints for malware samples: MD5/SHA-1/SHA-256 for exact identity, plus import hashing (imphash), section hashing, and fuzzy hashes (ssdeep, TLSH) to cluster related variants. Activates for requests to hash a sample, compute imphash, or fingerprint files for similarity clustering.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Extracts indicators of compromise from raw analysis artifacts: parsing strings dumps, sandbox reports, PCAP summaries, and logs for URLs, domains, IPs, hashes, mutexes, and file paths, then deduplicating and typing them. Activates for requests to extract IOCs from analysis output, pull indicators from a report, or harvest atomic indicators.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Enriches indicators with context from threat-intel sources: planning lookups against reputation, passive DNS, WHOIS, and sandbox/sample databases, scoring confidence, and avoiding operational-security mistakes that tip off adversaries. Activates for requests to enrich IOCs, add threat context, or plan indicator lookups safely.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Establishes a disciplined malware sample repository: content-addressed storage by hash, encrypted/password-protected archiving, consistent metadata records, and chain-of-custody tracking so samples are reproducible and safe to handle. Activates for requests to organize a malware repository, manage samples, or track sample metadata and provenance.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Collects volatile evidence from a potentially compromised host in correct order of volatility: memory, network state, running processes, logged-on users, and open handles, while preserving integrity and minimizing footprint. Activates for requests to collect volatile evidence, perform live response, or capture host state before shutdown.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Prepares indicators of compromise for safe sharing: defanging URLs, domains, IPs, and emails so they cannot be accidentally clicked or resolved, and formatting them into STIX/CSV/MISP-friendly output. Activates for requests to defang IOCs, sanitize indicators for a report, or export indicators for sharing.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新