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概要と使いどころ
Formal oracle for abductive inference that selects the minimal hypothesis best explaining a set of observations. Provides three sub-oracles: MCMC via monad-bayes, Gemini for natural language, and propagator networks for constraint domains. Use when performing hypothesis selection, explaining observations, or solving inference-to-best-explanation problems.
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 this skill when reviewing, designing, or improving a workshop, lesson, training session, facilitation plan, talk, or educational explanation. Use it when the user provides a topic, concept, or explanation and wants better framing questions, curiosity hooks, opening prompts, discussion questions, learner reflection prompts, or ways to make participants think before being taught.
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。
Configures pyproject.toml and Python packaging using PEP 517/518/621/660/723 standards. Use when creating or updating pyproject.toml, selecting a build backend (hatchling/setuptools/flit), configuring ruff, ty, mypy, pytest, or coverage tool sections, setting up dependency constraints or optional extras, defining CLI entry points, configuring pre-commit hooks, establishing src-layout directory structure, or preparing a package for PyPI publishing.
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。
Use when writing delegation instructions to subagents, authoring CLAUDE.md files, rules, skills, or agent definitions, or auditing existing AI-facing content for bloat. Activates on "write a rule for", "add to CLAUDE.md", "create an agent", "update memory", or any request to author AI-facing instruction content. Removes discoverable data, explained-away knowledge, invented constraints, and stale cached facts.
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。
Creative reasoning framework for ill-defined problems where conventional solutions are suboptimal. Use when the problem has ambiguous goals, vast solution space, no single correct answer, or requires innovation. Implements three paradigms — combinational (novel combinations of familiar ideas), exploratory (expand solution space boundaries), transformative (alter fundamental constraints). Do not use for well-defined problems, mathematical puzzles, or tasks requiring convergent 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。
Enforce anti-AI UI design rules based on the Uncodixfy methodology. Use when generating HTML, CSS, React, Vue, Svelte, or any frontend UI code. Prevents generic AI aesthetic — soft gradients, glassmorphism, hero sections in dashboards, oversized rounded corners, and decorative copy. Applies constraints from Linear/Raycast/Stripe/GitHub design philosophy for functional, honest, human-designed interfaces. Triggers on UI generation, dashboard building, component creation, CSS styling, landing page design, or any task producing visual interface code.
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。
Verifies claims in backlog items, skill documentation, or plugin content against primary sources using web lookups. Spawns parallel verification agents that must use WebFetch/WebSearch/gh — training data recall is explicitly rejected as evidence. Produces VERIFIED/REFUTED/INCONCLUSIVE verdicts with citations. Use when items are marked UNVERIFIED or when verifying tool API claims, CLI flags, or documented software 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。
This skill should be used when the user encounters "var-annotated" mypy errors, asks to "fix var-annotated errors", "add type annotations to variables", or mentions "Need type annotation for" errors. Provides workflow for fixing missing variable type annotations while respecting forbidden type constraints (no Any, dict[str, Any], list[Any], etc.).
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。
This skill should be used when the user asks to "fix mypy errors", "add type annotations", "fix type checking", "resolve no-untyped-def", "fix mypy type errors", or when working with type hints while respecting StreamFlow's forbidden type constraints (no Any, dict[str, Any], etc.).
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。
This skill should be used when the user encounters "no-untyped-def" mypy errors, asks to "fix no-untyped-def errors", "add type annotations to functions", or mentions "Function is missing a type annotation". Provides specific workflow for fixing missing type annotations while respecting forbidden type 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 systematic problem-solving techniques for marketing challenges including campaign complexity (simplification cascades), creative blocks (collision-zone thinking), recurring campaign patterns (meta-pattern recognition), assumption constraints (inversion exercise), audience scale uncertainty (scale game), and dispatch when stuck. Techniques derived from proven problem-solving frameworks adapted for marketing execution.
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。
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."
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 complete social media publishing calendar from a campaign goal, date range, audience, channels, and content constraints. Use when planning a week, month, launch window, or ongoing period of scheduled content.
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。
Write effective system prompts for TD AI agents. Covers role definition, constraint specification, output formatting, tool usage instructions, and prompt structure patterns.
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。
SQLite database expertise for migrations, multi-tenant patterns, transactional safety, FTS5 virtual tables, and schema evolution. Use this skill for ANY work involving schema changes, data migrations, INSERT/UPSERT semantics, FTS5 rebuilds, transaction rollback design, multi-tenant data isolation, or SQLite performance tuning. Triggers include: writing migration SQL, modifying `_import_table`-style importers, designing UNIQUE/PK constraints, adding indexes for JOINs, debugging "rows missing" / "wrong count" / "stuck for hours" symptoms in SQLite-backed systems.
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 the user has written (or wants to write) a `ModularPipelineBlocks` subclass in a local Python file and needs to package it into a Hub-uploadable directory. Covers the workflow from a single `block.py` file to a published custom-block repo that consumers can load via `ModularPipeline.from_pretrained(<repo>, trust_remote_code=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。
Research an issue deeply and present all context to the user. but the user writes the code. The LLM investigates code paths, finds relevant files, explains patterns, and identifies constraints. The user thinks through the approach and implements it. Use when ready to start working on an issue after oss-prep-to-contribute. Not for writing tests or documentation as a standalone contribution. Use oss-write-tests or oss-write-docs for those.
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。
Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.
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。
Odoo 19 development knowledge base covering actions, controllers, data files, API decorators, SQL constraints, indexes, modules, fields, manifests, mixins, ORM methods, migrations, OWL components, performance, QWeb reports, security, testing, transactions, translations, and XML views. Use when writing, reviewing, or debugging Odoo 19 Python, XML, or JavaScript code, creating or modifying modules, fixing performance issues, or looking up Odoo 19 API patterns and best practices.
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。
Trace Odoo execution flow from an entry point through controllers, button actions, cron jobs, model methods, overrides, computes, onchanges, constraints, database operations, security checks, and side effects. Use before implementation, during debugging, impact analysis, performance review, or code review when behavior depends on Odoo call chains.
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。
Odoo 20 development knowledge base covering actions, controllers, data files, API decorators, SQL constraints, indexes, modules, fields, manifests, mixins, ORM methods, migrations, OWL components, performance, QWeb reports, security, testing, transactions, translations, and XML views. Use when writing, reviewing, or debugging Odoo 20 Python, XML, or JavaScript code, creating or modifying modules, fixing performance issues, or looking up Odoo 20 API patterns and best practices.
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。
Expert sales enablement strategist for building high-performing sales teams. Use when designing sales training programs, onboarding and ramp plans, sales playbooks, coaching frameworks, certification programs, or competitive intelligence distribution. Covers content strategy, tool adoption, performance measurement, and continuous learning systems. Use for building sales academies, creating enablement content, and optimizing sales productivity.
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。