The Agentic AI Pattern That Always Keeps You Honest

The Evaluator-Optimizer is one of five workflow patterns Anthropic defines in Building Effective Agents: one LLM generates, another evaluates and provides feedback in a loop. Claude Code doesn't have that automatic loop — but you can build it as an inline skill invoked on demand.

The pattern's core: every claim from the previous output is checked against real evidence — source code, official documentation, configuration files. Not opinions. Verifiable facts.

Result:

/evaluate       # 1 evaluation pass
/evaluate 2     # 2 passes (the second evaluates the evaluation itself)

Why a skill, not a sub-agent

The evaluator needs to see what was just produced. A sub-agent or a skill with context: fork loses conversation context — it would have to rediscover everything from scratch.

flowchart TD
    A["Does the evaluator need to see\nthe previous output?"] -->|Yes| B["Inline skill"]
    A -->|No| C["Needs isolation?"]
    C -->|Yes| D[Sub-agent]
    C -->|No| E["Skill with context: fork"]

The official documentation backs this: "Consider Skills instead when you want reusable prompts or workflows that run in the main conversation context rather than isolated subagent context."

The skill

---
name: evaluate
description: Evaluator-Optimizer pattern. Critically evaluates every claim,
  decision, and assertion from the previous output against verifiable evidence
  from code, documentation, configuration, and other sources.
disable-model-invocation: true
argument-hint: [passes]
allowed-tools: Read, Grep, Glob, Bash, WebFetch, WebSearch
---

• disable-model-invocation: true — you decide when to evaluate, not Claude
• allowed-tools — the evaluator needs to read and search to verify claims
• $ARGUMENTS — /evaluate 2 runs two passes; no argument runs one

The verdict system

Rule: every verdict cites a specific source — file path with line number, URL, command output. "I believe" is not evidence. No source = UNVERIFIED.

In practice

I ran /evaluate on the very analysis that produced the skill. Result: 21 claims, 18 verified, 3 partially correct. None incorrect — but three solid assumptions had nuances I wouldn't have caught without the pattern. The full article covers the process end to end: Evaluator-Optimizer in Claude Code: From Pattern to Skill.

Official docs: Skills · Building Effective Agents — Anthropic