evaluator

Evaluate task outputs against Task.md Expected Results and generate evaluation.md.

3|3|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/hs3180/disclaude --skill evaluator-hs3180
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: evaluator
Source: https://github.com/hs3180/disclaude/tree/main/skills/evaluator
Command: npx skills add https://github.com/hs3180/disclaude --skill evaluator-hs3180

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill evaluates whether a task has been completed according to Task.md Expected Results, producing a structured evaluation and, when complete, a final result signal.

Core Features & Use Cases

  • Automatically compare Executor outputs to Task.md Expected Results and produce evaluation.md.
  • Create final_result.md when the status is COMPLETE to signal successful completion.
  • Enforce iterative workflow rules, including Next Actions, and document progress for auditability.
  • Provide deterministic guidance on what to change next and ensure safe, auditable outcomes.

Quick Start

Execute an evaluation cycle by reviewing the executor's output and writing an evaluation.md; if all criteria are met, also write final_result.md.

Frequently Asked Questions about evaluator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate task outputs against expected results in an iterative workflow?

To evaluate task outputs, you compare the executor's deliverables against the Task.md Expected Results and generate an evaluation.md file documenting the status and required next actions.

How does final_result.md signal task completion in an automated workflow?

Final_result.md signals task completion by acting as a deterministic success marker. It is only generated when the evaluation confirms all Expected Results criteria are fully met.

Do I need to manually write evaluation reports for iterative task assessments?

You do not need to manually write evaluation reports from scratch. The evaluation process automatically reviews executor outputs against criteria and enforces strict output conventions for evaluation.md.

What is the best way to document next actions when task outputs do not meet expected results?

The best way to document next actions is to include deterministic guidance within the evaluation.md. This ensures auditable progress tracking and explicitly states what changes are required for the next iteration.

Can I use this evaluation process for workflows without a predefined Task.md file?

You cannot use this evaluation process without a Task.md file. The mechanism strictly depends on comparing executor outputs against the Expected Results defined within Task.md to generate valid assessments.