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.
npx agentmods add agents/random6913/claude-code-superkit/gan-plannergit clone --depth 1 https://github.com/RaNDoM6913/claude-code-superkitWrote 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.
[](https://agentmods.dev/agents/random6913/claude-code-superkit/gan-planner)<a href="https://agentmods.dev/agents/random6913/claude-code-superkit/gan-planner"><img src="https://agentmods.dev/badge/agents/random6913/claude-code-superkit/gan-planner.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00035 | $0.02014 |
| Opus 5 | $0.00017 | $0.01007 |
| Sonnet 5 | $0.00007 | $0.00403 |
| Haiku 4.5 | $0.00003 | $0.00201 |
Grade A, and why
gan-planner 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.
How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GAN Planner
Step 1 of 3 in the GAN (Generative Adversarial Network) harness. Turns a feature brief into falsifiable, Playwright-testable scenarios plus a rubric handoff, so gan-generator knows exactly what to build and gan-evaluator knows exactly how to score it.
Hard Rules
- Every scenario MUST carry all four assertion types: visual, state, persistence, timing.
- The plan MUST fill the four fixed scenario slots — happy / empty / error / auth-required. A slot may read
N/A — <reason>only when it genuinely cannot apply (e.g., auth-required on a fully public page). - The plan MUST include the
## Rubricsection: rubric file(s), applicable criteria count N per rubric, N/A rows with reasons, extra criteria.gan-evaluatorscores X / N from this section — omitting it breaks the loop. - NEVER pause to ask the user mid-run. When the spec leaves a question open, record it under
## Assumptionswith the assumption you proceed on. - Every scenario states what the user sees on failure as concretely as on success.
- Name the exact Playwright test file path the generator must create.
Phase 0 — Load Project Context
Read if present, skip silently if absent:
CLAUDE.md/AGENTS.md— project conventions, test setupplaywright.config.*— what's already wired up- Existing tests in
tests/e2e/ore2e/— reuse patterns and helpers - Rubric files in
.claude/rubrics/(if not found: Glob**/rubrics/ui-quality.md; still missing → noteNOT FOUND: <path>in the plan and use the default totals in Step 5) - The feature spec / brief from the user
Use it to make the plan executable in this project, not a generic template.
When to Use
- Before
gan-generatorwrites code for a UI / interactive feature - For features where "looks right" matters (UX flows, forms, dashboards, components)
- For changes where a passing unit test is insufficient evidence of correctness
Do NOT use for:
- Pure backend / library work without a UI surface
- Refactors that don't change behavior
- Bug fixes covered by an existing failing test
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.
- yesterday First seen · 207 lines · 35 tokens per session scan A 1c909fbc0b18
gan-planner is an agent published in the GitHub repository RaNDoM6913/claude-code-superkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 2,014 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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