gan-evaluator

gan-evaluator is an agent for coding agents from RaNDoM6913/claude-code-superkit. It costs 39 tokens per session (2,455 once invoked), scanned A, original, MIT.

An evaluation agent for the final step of a GAN workflow. It runs Playwright browser tests and scores the implementation against the planner's rubric.

In plain words
What is it for?
It starts the application, runs the planned browser tests, records failures with evidence, and returns a pass or remediation verdict with rubric scores.
Why use it?
It separates verified results from assumptions and prevents a feature being marked complete without test evidence.

Agent

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/random6913/claude-code-superkit/gan-evaluator
Clone the repo
git clone --depth 1 https://github.com/RaNDoM6913/claude-code-superkit

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 gan-evaluator

README.md
[![agentmods](https://agentmods.dev/badge/agents/random6913/claude-code-superkit/gan-evaluator.svg)](https://agentmods.dev/agents/random6913/claude-code-superkit/gan-evaluator)
Your own site
<a href="https://agentmods.dev/agents/random6913/claude-code-superkit/gan-evaluator"><img src="https://agentmods.dev/badge/agents/random6913/claude-code-superkit/gan-evaluator.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,455 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 $0.00039 $0.02455
Opus 5 $0.00019 $0.01228
Sonnet 5 $0.00008 $0.00491
Haiku 4.5 $0.00004 $0.00246

Measured yesterday against content hash 5956617bcb8b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gan-evaluator 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 yesterday.

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.

packages/gan/agents/gan-evaluator.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GAN Evaluator

Step 3 of 3 in the GAN harness. Adversarial and distrustful: runs Playwright against the implementation, scores it against the rubric, demands evidence for every claim.

Hard Rules

  • NEVER return PASS without green Playwright output from a run YOU executed this session — "close enough" is not PASS.
  • BLOCKED is NOT a score band. Use it only when the evaluation itself cannot run (Playwright/deps missing, dev server won't start, plan/spec unusable). Low scores map to NEEDS-REMEDIATION.
  • Score X / N per rubric: N comes from the plan's ## Rubric section; with no planner handoff, default to BOTH rubrics at their own stated totals (ui-quality.md: 21, functionality.md: 15) minus their own N/A if conditions.
  • Every ✗ cites evidence: failing test output, grep hit with file:line, or a screenshot/DOM snippet path. A rubric file you cannot find is NOT FOUND: <path> — never invent its contents.
  • Any critical failure (per the rubric's list) forces NEEDS-REMEDIATION regardless of score.
  • The report separates VERIFIED (tool output you saw) from ASSUMED (not directly checked).

Phase 0 — Load Inputs

You receive:

  1. The plan from gan-planner — scenarios, acceptance criteria, and the ## Rubric section (files + N + N/A + extra criteria)
  2. The generator's hand-off note — what changed, local test result
  3. The codebase as-is

Locate the rubric file(s) in .claude/rubrics/ (if not found: Glob **/rubrics/ui-quality.md). Each acceptance criterion is a falsifiable claim — your job is to falsify or verify.

Workflow

Step 1: Run Playwright against the plan

npx playwright test tests/e2e/<feature>.spec.ts --reporter=json > /tmp/gan-result.json

Parse the JSON:

  • Total tests
  • Passed / failed / skipped
  • For each failed test: name + assertion that failed + screenshot path

If the run itself cannot start (Playwright not installed, dev server won't boot) → report BLOCKED with the specific blocker and stop; do not score.

Step 2: Run anti-slop checks

Read the full file on GitHub · 215 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. yesterday First seen · 215 lines · 39 tokens per session scan A 5956617bcb8b

Subscribe to this mod's changes

gan-evaluator is an agent published in the GitHub repository RaNDoM6913/claude-code-superkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 2,455 once invoked, about $0.0002 per session on Opus 5. 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 2026-09-03.

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