This skill should be used when the user wants to evaluate an AI agent end-to-end: scaffold an evaluation, design metrics that test a real hypothesis, make an agent measurable, audit generated eval config, read evaluation results, or run an improvement ("hill climbing") loop. Covers evaluation methodology, metric…
★not rated 3.1k▲
+3 3d agoASkillSpector: pass123 tokens
originalApache-2.0
Executes high-performance agent evaluations, multi-turn UserSim simulations, and declarative metric grading aligned with google/agents-cli and the Quality Flywheel. Publishes benchmark artifacts to the GCS Evaluation Registry, executes automated head-to-head delta comparisons (--compare-to), and optimizes system…
Performs an exhaustive, question-by-question narrative diagnostic breakdown of an agent-eval benchmark run by analyzing questionanswerlog.md, evalsummary.json, and raw trajectory traces. Use when diagnosing low score causes, investigating the Memory Reuse vs. Traceability rubric clash, performing pre-release failure…
★not rated 3.1k▲
+3 3d agoASkillSpector: pass100 tokens
originalApache-2.0
Uses Chrome DevTools via MCP for efficient debugging, troubleshooting and browser automation. Use when debugging web pages, automating browser interactions, analyzing performance, or inspecting network requests.
Git safety and operational guidance for Scion agents. Covers working tree resets, rebase pitfalls, and general git behavior that agents should know regardless of workspace mode. For workspace-mode-specific git rules, see the git-sandbox skill.
Git workflow protocol for agents in sandbox/worktree environments. Covers local-only operations, worktree-aware branch management, and non-interactive conflict resolution. Injected only for git-associated workspaces.
Operational constraints for Scion agents running in containerized sandboxes. Covers prohibited commands and hub-only API access. Complements the scion CLI reference and messaging skills.
How to use the scion message command effectively. Use this for communication with other agents or users. Covers recipient types, message timing, content best practices, and special message flags.
Schedule one-shot and recurring events for agents using the Scion CLI. Covers when to use scheduled events vs inline message delays, recurring cron schedules, lifecycle management, and the blocked-wait pairing rule.
Create or extend scion agent team templates from a high-level description of roles and workflow. Use when the user describes a multi-agent team, panel, crew, pipeline, or any scenario requiring coordinated LLM agents with distinct roles. Also use when adding new roles to an existing team, modifying workflows, or…
How to use the scion conversation command for managing conversations. Covers listing, creating, viewing, participant management, and message retrieval. Complements the scion-messaging skill.
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Generates a LiveAPI client service class in the user's chosen programming language. Use when the user wants to build, scaffold, or integrate a client that connects to the Gemini LiveAPI websocket endpoint (Gemini Enterprise or non-Gemini Enterprise), handles session setup/resumption, bearer token refresh, and…
Evaluate and improve GenAI models and agents using the Google GenAI Evaluation SDK. Creates eval datasets (from session traces or synthetic generation), selects and configures metrics (RubricMetric, LLMMetric, CodeExecutionMetric), executes evals via client.evals.evaluate(), and analyzes results to suggest concrete…
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: