Borrowing it
Nothing to install: this file belongs to hooyao/vortex-funnel-gen. 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/hooyao/vortex-funnel-gen/main/CLAUDE.mdgit clone --depth 1 https://github.com/hooyao/vortex-funnel-genWrote 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/hooyao/vortex-funnel-gen/claude-md)<a href="https://agentmods.dev/instructions/hooyao/vortex-funnel-gen/claude-md"><img src="https://agentmods.dev/badge/instructions/hooyao/vortex-funnel-gen/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/hooyao/vortex-funnel-gen/claude-md"><img src="https://agentmods.dev/badge/instructions/hooyao/vortex-funnel-gen/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 | $0.02116 | $0.02116 |
| Opus 5 | $0.01058 | $0.01058 |
| Sonnet 5 | $0.00423 | $0.00423 |
| Haiku 4.5 | $0.00212 | $0.00212 |
Grade A, and why
vortex-funnel-gen 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Language
- Reply in the language the user is currently using (Chinese -> Chinese, English -> English).
- Code, code comments, documentation files, and CLAUDE.md must always be written in English.
Project Purpose
Automated agentic optimization loop for designing an FDM 3D-printable fluid funnel (automotive windshield washer fluid). The system generates internal non-linear helical vane topologies that induce annular flow (stable central air core) to eliminate glugging during pouring. The optimization loop iterates: parametric geometry -> CFD simulation -> fitness evaluation -> next parameter set.
Architecture
The pipeline is a sequential three-stage loop orchestrated by optimization/loop.py:
optimization/loop.py (controller — multi-fidelity Bayesian optimisation)
|
+--> geometry/funnel_generator.py CadQuery: params (JSON) -> STEP + STL
|
+--> cfd/runner.py Docker OpenFOAM: copies base_case/,
| | injects STL, runs mesh -> solve,
| | extracts fitness via pyvista
| +-- cfd/base_case/ OpenFOAM template
| 0/ (alpha.water, U, p_rgh — uniform templates)
| constant/ (transportProperties, turbulenceProperties, g)
| system/ (controlDict, fvSchemes, fvSolution,
| blockMeshDict, snappyHexMeshDict,
| setFieldsDict, decomposeParDict)
|
+--> output/ Converged STLs + visualization data
+--> output/best_design/ Final optimised design (STL + STEP + CFD)
+--> output/optimisation/ Per-iteration results + history.json
Fitness metric: R = 0.50 * norm(air_core_diameter) + 0.30 * norm(throat_velocity) + 0.20 * air_fraction_throat. Extracted at the funnel throat (z=30mm) from interFoam VOF results via pyvista.
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 · 174 lines · 2,116 tokens per session scan A 3b87cb943efd
vortex-funnel-gen CLAUDE.md is an instructions file published in the GitHub repository hooyao/vortex-funnel-gen (5 stars, last pushed 4mo ago), licensed MIT. It adds 2,116 tokens to every session, about $0.0106 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.