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Trigger with "show me the improvement chart", "how are we improving", "progress report", "graph the eval scores", "show cycle of improvement", "what's the trend", "are we getting better". Produces a visual/text summary of how the agentic loop is improving across cycles. Do NOT use this to run the learning loop or evaluate a specific skill change.

Orchestrates the full prototype build cycle for a Subject Matter Expert. Coordinates layout confirmation and component building — it does not build components directly. Acts as the single entry point for all prototype-related requests. Trigger phrases: "build a prototype", "create a working prototype", "show me a working version", "prototype to clarify scope", "build an exploratory prototype"

Interactive skill to scaffold and optimize the .agents/ directory for any project mapping up Antigravity configuration. Sets up .gemini/GEMINI.md, skills/, prompts/, and config.json using best practices. Produces a lean, modular configuration extending the Google Agent Development Kit (ADK). Trigger with "set up antigravity", "scaffold .agents folder", "configure gemini for this project", or "crea

A package builder skill that compiles specs/ documents into standard spec-kits and scaffolds the clean target codebase sandbox.

Discovers and persists the user's available AI environments (Claude, Copilot CLI, Gemini CLI, Cursor, etc.) to context/memory/environment.md. Run once after OS setup or whenever the environment changes. os-architect and os-evolution-planner read this file to select the right delegation backend and cheapest brainstorm model automatically. Invoked by os-architect on first run if environment.md is ab

Activate when the user wants to install, deploy, test, or materialize an APM package into runtime directories such as .agents/, .github/, .claude/, .cursor/, .gemini/, .codex/, .opencode/, or .windsurf/. Use after creating or converting an APM package.

(Industry standard: Meta-Learning System / Automated Autoresearch) Primary Use Case: Continuous, self-improving orchestration of an agentic system over multiple sessions. Use when: building a continuous improvement layer that autonomously identifies workflow friction, postulates hypotheses, and tests improved instructions/coding skills against an objective headless benchmark before merging and per

A standard Spec-Kitty workflow routine.

Runs a semantic health check over the Obsidian LLM wiki using the cheapest available LLM CLI. Finds inconsistencies, missing concepts, stale articles, connection candidates, and new article suggestions. Writes a structured report to meta/lint-report.md. Use when the wiki is large enough to have quality drift, or as a periodic maintenance step.

Core markdown syntax skill for Obsidian. Enforces strict parsing and authoring of Obsidian proprietary syntax (Wikilinks, Blocks, Headings, Aliases, Embeds, Callouts). Use when reading, writing, or validating Obsidian-flavored markdown.

Safely removes all agent lock files from the context/.locks/ directory to resolve deadlocks caused by crashed agents leaving stale locks behind. Use when the user says "/os-clean-locks", "clear all locks", "reset agent locks", or when an agent is deadlocked and cannot acquire a lock because a previous agent crashed and left a stale lock behind in context/.locks/. Verifies lock existence, discovers

Builds an executable safety net of characterization tests by integrating browser flow recording, API payload snapshotting, DOM state captures, network traces, and mock fixture generation.