agent-self-evaluation

name	agent-self-evaluation
description	Self-rate output on 5 axes (accuracy, completeness, clarity, actionability, conciseness) after completing non-trivial tasks. Produces a structured 1-5 scorecard with improvement suggestions.
version	1.0.0
author	Hermes Agent (adapted from ECC)
license	MIT
platforms	["linux","macos","windows"]
metadata	{"hermes":{"tags":["quality","self-review","evaluation","reflection"],"related_skills":["verification-loop","eval-harness"]}}

Agent Self-Evaluation

After completing a complex task, pause to rate your output against a structured 5-axis rubric. This is NOT a pass/fail gate — it's a deliberate reflection step that catches omissions, flags overconfidence, and surfaces areas for improvement before the user has to.

When to Activate

• After writing code that spans 3+ files or 50+ lines
• After completing a multi-step workflow (implement → test → review)
• After a debugging session that involved 3+ attempts
• After producing a design document, architecture decision, or written analysis
• When the user asks "how good was that?" or "rate yourself"

The 5 Evaluation Axes

Axis	Question	What it catches
Accuracy	Are the facts, claims, and outputs correct?	Hallucinations, wrong API names, incorrect syntax, false statements
Completeness	Did it cover everything the user asked for?	Missed edge cases, unhandled error paths, forgotten requirements
Clarity	Is the explanation understandable and well-structured?	Confusing explanations, jargon, missing context, rambling
Actionability	Can the user act on the output immediately?	Vague suggestions, missing steps, no verification path
Conciseness	Did it use the minimum words/tokens needed?	Redundancy, over-explanation, filler content

Scoring Scale

5 — Exceptional: no reasonable improvement possible
4 — Good: minor nits only, no substantive gaps
3 — Adequate: meets the request but has a notable weakness on at least one axis
2 — Weak: has a clear gap that affects usability or correctness
1 — Poor: fundamentally misses the request or contains significant errors

The Evidence Rule

Every score below 5 MUST cite specific evidence. A score of 3 cannot just say "could be better" — it must say exactly what is missing or wrong. "Show the gap, don't just name it."

Workflow

Step 1: Collect the Raw Material

• The original user request
• Your final response/output
• Any tool outputs that verify correctness (test results, exit codes, lint output)
• Any user feedback received during the task

Step 2: Score Each Axis Independently

Work through the 5 axes one at a time. Score each axis fresh — don't pre-average.

Step 3: Produce the Evaluation Report

Scorecard:
  Accuracy:    X — [evidence]
  Completeness: X — [evidence]
  Clarity:     X — [evidence]
  Actionability: X — [evidence]
  Conciseness: X — [evidence]

Overall: X.X / 5

Top improvements:
1. [highest impact fix]
2. [next]
3. [next]

Step 4: Apply the Improvement

If any axis scored 3 or below:

• State what you would do differently
• If gap is fixable in < 30 seconds, fix it now
• If gap requires rework, flag it explicitly

Hermes Integration

• Run after delegate_task completes for subagent quality check
• Run after significant write_file or replace_string_in_file operations
• Combine with verification-loop for comprehensive quality gates
• Combine with eval-harness for formal evaluation tracking