Browse skills

Use when validating, auditing, or verifying IFC model quality in Bonsai projects. Provides systematic checks for spatial hierarchy completeness, property set compliance, geometry validity, classification correctness, and IDS (Information Delivery Specification) conformance using ifctester. Prevents shipping models with missing spatial containment or incomplete property sets. Keywords: IFC validation, audit, quality check, spatial hierarchy, property set, IDS, ifctester, model quality, Bonsai validation, compliance, check my IFC file, is my model correct, find errors.

Use when reviewing, validating, or auditing IfcOpenShell Python code for correctness. Runs systematic checks for schema compatibility errors, incorrect API usage (direct attribute modification vs api.run), entity reference invalidation, performance anti-patterns, and IFC standard compliance. Prevents shipping code that works on one schema but fails on another. Keywords: code review, validation, audit, IfcOpenShell, API usage, schema compatibility, entity reference, performance, code quality, check my IFC script, review IfcOpenShell code.

Use when reviewing, validating, or auditing Sverchok node code for correctness. Runs 19 automated checks covering data nesting correctness, updateNode callbacks, list matching patterns, socket consistency, import validation, and IfcSverchok compliance. Prevents shipping node code with silent data corruption or missing update triggers. Keywords: Sverchok validation, code review, data nesting check, updateNode check, socket consistency, import validation, IfcSverchok compliance, code quality, my node has errors, check node code.

Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

Use when testing agent without context validation

Use when testing context without agent validation

Use when testing invalid agent validation

Detect agentic coding infrastructure in a project: CLAUDE.md, AGENTS.md, installed skills, MCP servers, hooks, and cross-tool compatibility (Claude Code and Codex CLI). Returns structured findings about agentic readiness without applying changes. Use when the user asks to "review agentic setup", "check agentic setup", "agentic readiness", "is this project set up for AI coding", or "review AI coding setup".

Build multi-agent AI systems with Microsoft's Agent Framework (formerly Semantic Kernel Agents). Use when: defining AI agents, orchestrating multi-agent workflows (sequential, parallel, conditional), creating custom agents in Python or .NET, using built-in agents (ChatCompletion, OpenAI Assistant), deploying agent systems, or comparing agent orchestration patterns.

Meta-skill for discovering and invoking the right agent skill for any task. Use when starting a session, when unsure which skill applies, or when you need to understand the development lifecycle and how skills chain together. Covers skill discovery, core operating behaviors, and failure modes to avoid.

Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.