Build text and data classification systems with training and evaluation. TRIGGERS - Use when user needs help with ai-classification-system related tasks.
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。
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概要と使いどころ
Build text and data classification systems with training and evaluation. TRIGGERS - Use when user needs help with ai-classification-system related tasks.
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。
Query Strava fitness data including activities, athlete stats, segments, routes, clubs, and gear. Use when the user asks about cycling, running, swimming, workouts, training, or Strava data.
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。
Inventory all founder resources across 8 categories for a one-person company. Use when Codex needs to systematically confirm what resources the founder has — experience, network, skills, relationships, channels, assets, time/money constraints, hard limits — by first doing a broad scan of each category, then drilling into specifics (distribution, usable portions, how to use, cost of use), and producing a confirmed detailed resource inventory written to `opc-doc/`. Does NOT analyze directions, preferences, suitability, or risk tolerance — those belong to downstream skills.
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 a personal voice profile so Cowork writes the way you write — not like a generic AI. Use when personalizing your writing style, for capturing your communication patterns and tone, during setup after getting generic-sounding output, when training Cowork to match your voice, or when the user says "teach claude my voice", "my writing style", "output doesn't sound like me", "brand voice", "personalize output", "make it sound like me", "it sounds too formal", "it sounds too robotic", "can cowork match my tone", or "how do I get cowork to write like me".
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。
Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"
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 needing 100% type-safe, schema-valid data extraction from LLMs. Keywords: structured output, JSON schema, Pydantic, Zod, type-safe, constrained decoding, validation, tool use.
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。
Create/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.
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。
Generates Claude Code plugin agent .md files: writes YAML frontmatter (name, model, color, tools, hooks, disallowedTools), crafts system prompts, and creates triggering example blocks with context and commentary. Validates agent structure against naming, length, and format constraints. Use when the user asks to create an agent, add an agent, write a subagent, configure agent frontmatter, design agent system prompts, set agent tools or colors, build an autonomous agent, or add agent hooks.
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。
MATLAB R2026a workflow for signal processing, DSP, image processing, computer vision, lidar, medical imaging, deep learning, and AI-assisted reproducible experiments. Use for filters, spectrograms, wavelets, object detection, segmentation, classification, training, inference, and generated figures.
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。
MATLAB R2026a workflow for control systems, system identification, robust control, MPC, Simulink Control Design, parameter tuning, constrained optimization, and numerical validation. Use whenever the user asks for controllers, transfer functions, state-space models, tuning, identification, optimal control, or solver-based engineering.
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。
Pressure-test an assumption, decision, or inherited constraint — Socratic cross-examination that forces you to defend or abandon your position
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。
Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name.
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。
"Apply Giddens' structuration theory to analyze the duality of structure — how social structures are both the medium and outcome of the practices they organize. Use this skill when the user needs to bridge agency and structure in organizational or social analysis, explain how routines reproduce or transform institutional patterns, analyze the recursive relationship between action and structure, or when they ask 'do people shape institutions or do institutions shape people', 'how are these routines maintained', or 'where does change come from if structures constrain action'.".
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。
"Apply Upper Echelons Theory (Hambrick and Mason, 1984) to analyze how top management team characteristics — demographics, experiences, values — shape strategic choices and organizational outcomes. Use this skill when the user needs to evaluate TMT composition effects on strategy, predict strategic direction from leadership profiles, assess whether managerial discretion enables or constrains executive influence, or when they ask 'does leadership background matter for strategy', 'how does TMT composition affect decisions', or 'why did this management team make that choice'.".
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。
"Apply Bhaskar's critical realism to analyze phenomena through three ontological domains (real, actual, empirical), identify generative causal mechanisms via retroduction, and examine structure-agency interplay. Use this skill when the user needs to go beyond surface correlations to underlying causes, design research that distinguishes mechanisms from events from experiences, or when they ask 'what causes this beyond the observed pattern', 'what structures enable or constrain this behavior', or 'how do I move from correlation to causal explanation'.".
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。
"Apply mechanism design (reverse game theory) to engineer incentive-compatible rules for allocation problems. Use this skill when the user needs to design auctions, voting systems, or matching markets, or when evaluating whether a proposed mechanism satisfies incentive compatibility and individual rationality constraints.".
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。
"Apply social capital theory (Putnam, Coleman, Bourdieu, Burt) to analyze how network structures and trust generate value or impose constraints. Use this skill when the user needs to evaluate bridging vs bonding capital, identify structural holes or network closure benefits, assess community or organizational trust dynamics, or when they ask 'how does our network create value', 'are we too insular', or 'where are the structural holes we can exploit'.".
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。
"Apply Cognitive Load Theory to optimize instructional design by managing intrinsic, extraneous, and germane load within working memory limits. Use this skill when the user needs to diagnose why learners are overwhelmed, redesign training or documentation for better comprehension, evaluate UI/UX information architecture for cognitive burden, or when they ask 'why is this tutorial confusing', 'how to simplify complex instructions', or 'what causes information overload'.".
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。
"Apply AI ethics frameworks (fairness, accountability, transparency, privacy) to evaluate AI systems for algorithmic bias, explainability gaps, and value alignment failures. Use this skill when the user needs to audit an AI system for ethical risks, design fairness constraints, assess explainability requirements, or when they ask 'is this AI system fair', 'how do we detect algorithmic bias', 'what are the ethical implications of this AI deployment', or 'how do we make this model explainable to stakeholders'.".
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。
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts. Use when creating brand-kit image prompts, identity boards, logo systems, or visual-world presentations.
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。
Create or evaluate an architecture decision record (ADR). Use when choosing between technologies (e.g., Kafka vs SQS), documenting a design decision with trade-offs and consequences, reviewing a system design proposal, or designing a new component from requirements and constraints.
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。
"Solve vehicle routing problems to optimize delivery routes under capacity and time constraints. Use this skill when the user needs to plan delivery routes, minimize transportation costs, or optimize fleet utilization — even if they say 'delivery route optimization', 'fleet routing', or 'minimize driving distance'.".
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。
"Solve the influence maximization problem to select optimal seed nodes for maximum information spread. Use this skill when the user needs to choose seed users for viral campaigns, maximize network reach under a budget constraint, or compare seeding strategies — even if they say 'who should we seed first', 'maximize viral reach', or 'optimal influencer selection'.".
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。
"Optimize advertising budget allocation across campaigns using marginal returns analysis. Use this skill when the user needs to distribute budget across multiple campaigns, optimize spend pacing, or maximize overall ROAS under budget constraints — even if they say 'how to split my ad budget', 'campaign budget optimization', or 'diminishing returns on ad spend'.".
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。