Borrowing it
Nothing to install: this file belongs to yingying-chu/class-action-finder. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yingying-chu/class-action-finder/main/CLAUDE.mdgit clone --depth 1 https://github.com/yingying-chu/class-action-finderWrote 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/instructions/yingying-chu/class-action-finder/claude-md)<a href="https://agentmods.dev/instructions/yingying-chu/class-action-finder/claude-md"><img src="https://agentmods.dev/badge/instructions/yingying-chu/class-action-finder/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/yingying-chu/class-action-finder/claude-md"><img src="https://agentmods.dev/badge/instructions/yingying-chu/class-action-finder/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.02942 | $0.02942 |
| Opus 5 | $0.01471 | $0.01471 |
| Sonnet 5 | $0.00588 | $0.00588 |
| Haiku 4.5 | $0.00294 | $0.00294 |
Grade A, and why
class-action-finder CLAUDE.md 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This repo contains a single portable skill for capable AI assistant and agent environments in skills/class-action-finder/. ChatGPT, Claude, and Codex are the currently packaged and tested integrations, not the boundary of the core workflow. Run ./install.sh to install it into Claude's global skills directory (~/.claude/skills/). Use ./install.sh --codex for Codex.
The skill
class-action-finder does three jobs that feed each other, in one SKILL.md:
- Find notices — scans the user's connected email for direct class action settlement notices and produces a styled HTML report (
SKILL.mdPart A) - Match purchases — extracts minimal, non-sensitive evidence from purchase confirmations and checks public sources for potentially matching open settlements (
SKILL.mdPart D) - Remember — reads and writes a persistent record of what the user has filed and been paid (
SKILL.mdPart B), and can refresh the current report after a correction without re-scanning email (Part C)
Purchase Match is deliberately separate from direct-notice discovery. It uses a source badge plus a categorical eligibility match, never treats a receipt as proof of class membership, never sends personal receipt details to web search, and does not persist purchase history automatically.
Architecture
Connected mail
│
├── Direct notices (SKILL.md Part A)
│ Search inbox, spam, and promotions
│ Verify case and score legitimacy
│ Extract deadlines, payouts, IDs, PINs, and claim URLs
│
└── Purchase confirmations (SKILL.md Part D)
Extract merchant, product, and purchase date only
Search verified public settlement sources
Compare product, class period, and eligibility facts
│
▼
Match settlement identity
│
┌─────┴─────┐
▼ ▼
Tracker JSON HTML report
filed + paid actions + reviews + alerts
│ │
└─ refresh ─┘ (SKILL.md Parts B and C)
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.
- 9d ago First seen · 142 lines · 2,942 tokens per session scan A ed5244aad359
class-action-finder CLAUDE.md is an instructions file published in the GitHub repository yingying-chu/class-action-finder (3 stars, last pushed 15d ago), licensed MIT. It adds 2,942 tokens to every session, about $0.0147 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 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.