Use this to measure whether an AI agent actually completed its task end to end, not just whether individual LLM calls looked fine. Trigger on "is my agent working", "measure agent success rate", "evaluate my agent", "how good is my agent", "agent completion rate", or evaluating a multi-step/tool-using agent. Score the outcome of the whole task, plus the path it took.
How to install measure-agent-task-success?
contextjet-ai/awesome-llm-observability/measure-agent-task-success
$npx -y skills add contextjet-ai/awesome-llm-observability --skill measure-agent-task-successInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/contextjet-ai/awesome-llm-observability" --skill "contextjet-ai/awesome-llm-observability/measure-agent-task-success"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/contextjet-ai/awesome-llm-observability" that are relevant to the current task. Run `npx skills add "https://github.com/contextjet-ai/awesome-llm-observability"` and select the relevant skills, then follow their instructions.
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