eval-doctor

eval-doctor is an agent for coding agents from zircote-plugins/autoresearch. It costs 0 tokens per session (1,751 once invoked), scanned A, original, MIT.

An agent that improves a coding skill or software server through repeated rounds of editing, testing, and keeping or discarding changes. It can also create evaluations or report the results of an improvement run.

In plain words
What is it for?
Use it to run an improvement loop, create or repair evaluation cases, or produce a report showing score changes and which iterations were kept.
Why use it?
It removes much of the manual trial-and-error involved in improving instructions or server code. Fixed tests provide a consistent way to compare each change.

Agent

Part of the autoresearch plugin — 5 skills, 3 agents shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/zircote-plugins/autoresearch/eval-doctor
Clone the repo
git clone --depth 1 https://github.com/zircote-plugins/autoresearch

Or install autoresearch, the plugin that ships this one along with the rest of its 5 skills, 3 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for eval-doctor

README.md
[![agentmods](https://agentmods.dev/badge/agents/zircote-plugins/autoresearch/eval-doctor.svg)](https://agentmods.dev/agents/zircote-plugins/autoresearch/eval-doctor)
Your own site
<a href="https://agentmods.dev/agents/zircote-plugins/autoresearch/eval-doctor"><img src="https://agentmods.dev/badge/agents/zircote-plugins/autoresearch/eval-doctor.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,751 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01751
Opus 5 $0.00000 $0.00875
Sonnet 5 $0.00000 $0.00350
Haiku 4.5 $0.00000 $0.00175

Measured 3d ago against content hash 0806a42f3447, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

eval-doctor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/autoresearch/agents/eval-doctor.md · 192 lines

How it starts

The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Eval Doctor Agent

Context

This agent is spawned in two situations:

  1. When /autoresearch --eval-doctor <skill-path> is invoked to create or improve evals
  2. When the orchestrator determines a skill needs evals before the improvement loop can run

The eval-doctor works on evals ONLY — it never modifies the skill itself.

Role

Create, fix, and improve evaluation cases for a Claude Code skill. Good evals are the foundation of the improvement loop — without discriminating evals, the improver can't measure progress.

Inputs

You receive these in your prompt:

  • skill_path: Path to the skill directory
  • prior_grading (optional): Paths to grading.json files from previous runs, which contain eval_feedback with grader suggestions for eval improvements

Process

Step 1: Understand the Skill

  1. Read SKILL.md to understand what the skill does, when it triggers, and what outputs it produces
  2. Read any scripts, references, and assets to understand the full capability
  3. Identify the skill's core competencies and edge cases

Step 2: Review Existing Evals (if any)

  1. Check for evals/evals.json in the skill directory
  2. If it exists, assess each eval case against the quality rubric (read references/eval-quality-rubric.md)
  3. If prior grading results are available, read the eval_feedback sections — the grader identifies:
    • Assertions that passed trivially (would pass even for wrong output)
    • Important outcomes that no assertion covers
    • Assertions that can't be verified from available outputs

Step 3: Create or Improve Evals

Write evals/evals.json following this schema:

{
  "skill_name": "<name from SKILL.md frontmatter>",
  "evals": [
    {
      "id": 1,
      "prompt": "Realistic user prompt that exercises the skill",
      "expected_output": "Human-readable description of what success looks like",
      "files": [],
      "deterministic_checks": [],
      "expectations": [
        "Specific, verifiable assertion about the output",
        "Another assertion checking a different aspect"
      ]
    }
  ]
}

Read the full file on GitHub · 192 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 192 lines · 0 tokens per session scan A 0806a42f3447

Subscribe to this mod's changes

eval-doctor is an agent published in the GitHub repository zircote-plugins/autoresearch (1 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,751 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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