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MONAD-grounded cognitive architecture for AI memory as morphemic substrate navigation. Memory is not storage but substrate sampling - accessing the same structure that underlies reality. Implements φ-scaling, G...
Search and retrieve context from previous Angainor iteration transcripts. Use when you need detailed context about what happened in a previous iteration beyond what's in progress.txt. Triggers on: read transcri...
Build production-ready AI agents using Claude Agent SDK (Python). Use when implementing agent workflows, SDK integration, one-shot queries, interactive conversations, custom MCP tools, permission control, CLAUD...
Generates high-quality, predictable, and efficient .agent/skills/ directories based on user requirements. Use when the user wants to create a new skill or modify an existing one.
MONAD-grounded cognitive architecture for AI memory as morphemic substrate navigation. Memory is not storage but substrate sampling - accessing the same structure that underlies reality. Implements φ-scaling, G...
This skill should be used when building production LLM applications in any language. It applies when implementing predictable AI features, creating structured interfaces for LLM operations, configuring language...
A definitive guide to building multi-agent systems using the `openai-agents` SDK, enforcing live documentation retrieval via Context7.
How to create new skills following the agentskills.io specification
Implement RAG (Retrieval-Augmented Generation) patterns using Azure AI Search. Covers three retrieval approaches - (1) Agentic Retrieval for complex multi-query LLM-assisted search with knowledge bases, (2) Ful...
Run Claude Code programmatically via CLI (-p flag), Python SDK, or TypeScript SDK. For automation, CI/CD, session chaining, headless execution, and orchestrating multiple Claude instances. Triggers: programmati...
Use this skill to generate high-quality images, icons, and assets for frontend web development using Gemini 3 Pro.
TanStack Table で勤怠一覧/勤務表を作る。列定義、ソート/フィルタ、ページング、集計行、アクセシビリティ、CSV出力の型を固定する。キーワード: TanStack Table, table, columns, sorting, filtering, CSV
Design and generate visual dashboards to present pilot insights and trends. Use when creating executive summaries, interactive or static dashboard layouts, and report visualizations for stakeholder review.
Define measurable success metrics, KPIs, and acceptance criteria aligned to pilot objectives. Use when establishing evaluation frameworks, go/no‑go thresholds, or performance benchmarks based on pilot goals and...
Chart.js integration patterns for creating interactive statistical graphs in Django templates. Covers HTML setup, data injection, and JavaScript chart rendering with datalabels plugin.
Create minimalist, mobile-first Home Assistant dashboards using the Mushroom cards ecosystem (13+ card types) with card-mod styling. Use when building modern HA dashboards, creating compact mobile interfaces, s...
Run accuracy evaluation/tuning for RQ-SCAN and generate reports.
Map pilot outcomes to strategic benefits, ROI estimates, and KPI alignments to demonstrate value realization. Use when quantifying business impact, calculating return on investment, and aligning pilot results w...
Generates The Edmund Bogen Team's weekly market intelligence package: email, article page, dashboard, and community listings pages. Guides team through data collection, validates consistency, and produces all H...
Configure conditional visibility for Home Assistant dashboard cards based on entity states, numeric values, screen size, users, time, and complex logic (and/or). Use when hiding/showing cards dynamically, creat...
Run MOSAIC microsimulation and extract formatted results for paper
Display structured data in Textual using tables, lists, trees, and scrollable containers. Use when rendering data tables, building list views, displaying hierarchical data, scrolling large content, pagination,...
Econometric analysis, statistical inference, and empirical economics. Use for regression, causal inference, IV, DID, RDD, time series, panel data, or hypothesis testing.
Combine outputs from multiple instances into unified view, preserving diversity
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.