Open source alternatives to google-agents-cli-eval
24 open source AI Skills apps to use instead, best rated first.
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github-ops
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opensource-pipeline
Launchopensource-pipeline is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It prepares a private project for safe public release through a three-stage pipeline. The fork stage strips secrets from a copy. The sanitise st
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andrej-karpathy-skills
Launchandrej-karpathy-skills is a single CLAUDE.md file from the multica-ai project that is meant to improve how Claude Code behaves on coding tasks. It is derived from Andrej Karpathy's public observations about LLM coding pitfalls. The file dis
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microsoft/markitdown
Launchmarkitdown-mcp is the MCP server package for MarkItDown, Microsoft's tool for converting many file formats to Markdown for language models. It is a lightweight server that runs over stdio, Streamable HTTP or SSE, and exposes one tool, conve
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od-contribute
Launchod-contribute is an agent skill in the OpenDesign project that provides a guided, one-click contribution flow to the OpenDesign repository, written so that people without a coding background can send a real pull request. It is locked to the
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github-deep-research
Launchgithub-deep-research is an agent skill from the DeerFlow project that researches a single GitHub repository in several rounds and writes a report in Markdown. It is for requests that need more than a README summary, such as a comprehensive
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by shareAI-lab - A really interesting analysis of how coding agents like Claude
About google-agents-cli-eval

google-agents-cli-eval
Evaluate ADK agents with metrics, evalsets, and the iterative eval-fix loop
google-agents-cli-eval is an agent skill from Google's agents-cli project for evaluating Agent Development Kit (ADK) agents. It covers metrics, evaluation sets and an iterative eval-and-fix loop, in which the agent runs an evaluation, reads the results, changes the agent and runs it again. Evaluations run with the agents-cli eval run command, which chains generation and grading. The criteria are configurable and include tool trajectory, response matching, rubric-based scoring, hallucination detection and safety checks. Match types are EXACT, IN_ORDER and ANY_ORDER. The skill has references for the canonical evaluation dataset schema, with examples for single-turn, multi-turn and multi-agent cases and a list of common mistakes; a complete metrics guide that includes custom metrics and judge model configuration; user simulation for dynamic conversation testing; how built-in tools such as Google Search behave in evaluations; multimodal inputs; and live and voice agents. If the project was scaffolded with the scaffold skill, a dataset and a custom metric already exist in the tests/eval folder for Python projects.
- Price
- Free
- Made by
- Category
- AI Skills
- Website
- github.com/google/agents-cli/google-agents-cli-eval











