vortex-funnel-gen: Instructions file for Claude Code

CLAUDE.md

vortex-funnel-gen CLAUDE.md is an instructions file for Claude Code from hooyao/vortex-funnel-gen. It costs 2,116 tokens per session, scanned A, original, MIT.

Repository instructions for an automated design system that improves a 3D-printable fluid funnel through repeated geometry generation, fluid-flow simulation, and evaluation.

In plain words
What is it for?
Working on the funnel generator, computational fluid-dynamics runner, optimization loop, or related documentation and code.
Why use it?
It gives a coding agent the project’s language rules, purpose, architecture, and technology choices so changes fit the existing optimization workflow.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is hooyao/vortex-funnel-gen's own configuration. It tells Claude Code how to work on vortex-funnel-gen itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything vortex-funnel-gen configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/hooyao/vortex-funnel-gen/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/hooyao/vortex-funnel-gen

Made for: Claude Code.

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Per session 2,116 This file is loaded in full into every session.
When invoked 2,116 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.02116 $0.02116
Opus 5 $0.01058 $0.01058
Sonnet 5 $0.00423 $0.00423
Haiku 4.5 $0.00212 $0.00212

Measured 9d ago against content hash 3b87cb943efd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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.

CLAUDE.md · 174 lines

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.

Read the full file on GitHub · 174 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. 9d ago First seen · 174 lines · 2,116 tokens per session scan A 3b87cb943efd

Subscribe to this mod's changes

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.

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