agent-self-evaluation

Editorial and source context

What this Skill does

Agent Self Evaluation is a source-indexed Agent Skill for data, research & analysis work. Based on the SKILL.md description, it focuses on use after completing any non-trivial task. Use the linked GitHub file to confirm scope and prerequisites before enabling it.

What the author says

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

Compatibility and requirements

• Use an agent runtime that supports Agent Skills and the linked SKILL.md format.
• Confirm the source repository's tools, SDKs, and platform prerequisites for agent workflows work.

How to install or import it

• Open the linked GitHub SKILL.md and review its scope and setup instructions.
• Install or import the skill using the agent runtime's documented workflow.
• Run a small, non-sensitive test and verify the output before broader use.

Permissions and risks

• Review every command, file path, network request, dependency, and credential scope before enabling it.
• GitHub stars indicate popularity, not safety or correctness; validate the source and test with non-sensitive data.

Example workflows

• Ask an AI agent to apply Agent Self Evaluation to agent workflows work described in the source record.
• Have the agent state assumptions, required tools, and expected output before using this data, research & analysis skill.
• Compare the result with the linked GitHub SKILL.md and verify it against your project requirements.