Autonoma-AI

Read this skill when working on the planner CLI's eval harness (apps/cli/evals) - the SDK-integration eval, the planner-step evals, the artifact bootstrap - or when adding/capturing a new eval case. Covers the two eval layers, how a case is structured, how to run each eval, and how to author a new case + rubrics.

Always read this skill before editing any file under packages/ai/ or packages/visual-ai/. Covers AI primitives: the agent abstraction, model registry, structured output generation, visual checkers, and element detection used across the platform.

Watch a PR's OpenCode review and notify the user when it finishes. Polls the OpenCode workflow run (opencode-review.yml, or the /oc-triggered opencode-comment.yml) until it settles - following supersede when a new push cancels an in-flight review - then reads OpenCode's comment, summarizes its findings, and pings the user via their preferred method (default: a completion chime + treemux attention + an in-chat summary). Use when the user wants to be told when the OpenCode bot is done reviewing a PR, e.g. 'watch the opencode review and let me know when it's done', 'ping me when opencode finishes on PR 1485'.

Always read this skill before editing any file under apps/ui/. Contains all UI conventions, data fetching patterns, design system rules, and component guidelines for the Vite + React 19 SPA.

Orientation and playbook for investigating a diff job (DiffsJob) execution from production logs and the database - the trigger chain, Temporal workflow lifecycle, data model, where logs and agent conversations live, and how to correlate them. Use when investigating a specific diff job or snapshot, a missing/stuck/duplicate snapshot, affected tests or newly authored tests, a generation/replay/refinement outcome, or any diffs-analysis / worker-diffs / refinement-loop behavior. Read REFERENCE.md for table schemas, query recipes, and Sentry recipes.

Always read this skill before editing any file under packages/ai/. Covers AI primitives: the agent abstraction, model registry, structured output generation, visual checkers, and element detection used across the platform.

Always read this skill before editing any file under packages/engine/. Covers the platform-agnostic execution agent, command system, driver interfaces, and runner that engine-web (Playwright) and engine-mobile (Appium) extend.

Read this skill when working on scenario provisioning, the @autonoma/scenario package, the customer SDK endpoint contract, scenario recipe ingestion, scenario instance lifecycle, or any code that reads/writes the Scenario / ScenarioInstance / ScenarioRecipeVersion / WebhookCall tables.

Generates E2E test cases for a codebase through a validated multi-step pipeline. Each step runs in an isolated subagent and must pass deterministic validation before the next step begins. Use when the user wants to generate tests, create test scenarios, or build a test suite for their project.

Generates focused E2E test cases for a user-defined topic through a validated multi-step pipeline. Each step runs in an isolated subagent and must pass deterministic validation before the next step begins. When scenarios already exist in Autonoma, fetches context from the API and runs only Step 3 scoped to the topic. On a first run, executes the full 4-step pipeline with Step 3 focused. Use when you want targeted test coverage for a specific feature or domain.

Generate a complete E2E test suite for any web application using Autonoma's 4-step workflow: knowledge base generation, test data scenarios, E2E test case generation, and Environment Factory implementation. Use when the user wants to set up Autonoma testing, generate E2E tests, or implement the Environment Factory for their application.