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Found 38 Skills
Autonomous skill creation agent that analyzes requests, automatically selects the best creation method (documentation scraping via Skill_Seekers, manual TDD construction, or hybrid), ensures quality compliance with Anthropic best practices, and delivers production-ready skills without requiring user decision-making or navigation
A meta-skill for creating, documenting, and refining other Antigravity skills. Use this when the user wants to codify a workflow, automate a repetitive task, or save a successful interaction pattern as a permanent capability.
Generates high-quality Gherkin (BDD) scenarios from functional requirements using a two-agent iterative cycle: a generator agent that creates/modifies the Gherkin and a reviewer agent that validates it and proposes improvements. The cycle repeats automatically until the Gherkin passes review. Use this skill whenever the user mentions: "generate Gherkin", "BDD scenarios", "Gherkin test cases", "Feature/Scenario/Given/When/Then", "requirements to Gherkin", "BDD specifications", or asks to transform functional requirements into behaviour tests. Also applies when the user brings a requirements document and wants test cases, acceptance criteria, or user stories with executable examples.
Create custom multi-agent workflows for Atomic CLI using the defineWorkflow() session-based API with programmatic SDK code. Use this skill whenever the user wants to create a workflow, build an agent pipeline, define a multi-stage automation, set up a review loop, or connect multiple coding agents together. Also trigger when they mention workflow files, .atomic/workflows/, defineWorkflow, or ask how to automate a sequence of agent tasks — even if they don't use the word "workflow" explicitly.
Issue quality primitives: lint, enrich, decompose. `/issue lint [#N|--all]` — Score issues against org-standards. `/issue enrich [#N]` — Fill gaps with sub-agent research. `/issue decompose [#N]` — Split oversized issues into atomic sub-issues.
Resume work from a previous session, restoring context after a break, continuing work after /clear, or picking up where you left off. Triggers include "resume work", "continue work", "pick up where I left off", "restore context", and "resume session".
This skill should be used when the user asks to refactor specific files or directories, simplify recently changed code, clean up dead code in a limited scope, or invokes `/refactor` with paths or semantic queries.
Transform messy work updates into clean, standardized end-of-day Slack sync summaries. Use when asked to "format my updates", "create a sync", "write a standup", or "summarize my work" for Slack.
Migration workflow - research → analyze → plan → implement → review
Autonomous Goal-directed Iteration. Apply Karpathy's autoresearch principles to ANY task. Loops autonomously — modify, verify, keep/discard, repeat. Supports optional loop count via Claude Code's /loop command.
Detect new or modified skills in .agents/skills/ by comparing git hashes against ai-skills, snapshot for rollback, review, publish to ai-skills, install locally, and cherry-pick lockfile to TARGET. Replaces /elevate-skill.
Build and maintain a Karpathy-style LLM knowledge base — a self-compiling Obsidian markdown wiki where an Agent ingests raw sources, compiles cross-linked concept/entity/summary pages, answers queries against the corpus, lints the graph for health, and audits in-context human feedback filed from Obsidian or the local web viewer. Use when (1) scaffolding a new knowledge base for any research topic, (2) ingesting articles/papers/PDFs/web pages into raw/, (3) compiling or restructuring wiki articles from existing raw material, (4) answering questions against the wiki and filing durable answers back, (5) running lint passes for dead links / orphan pages / coverage gaps / audit shape, (6) processing human feedback from the audit/ directory and applying corrections. Not for general note-taking, daily journals, or non-wiki Obsidian use.