scaffold-python-experiment

scaffold-python-experiment is a skill for Claude Code, Codex from neha2110/brainstorming-buddy-template. It costs 67 tokens per session (1,016 once invoked), scanned C, original, no licence file.

A setup tool for starting a Python experiment or project with a standard folder layout, a Conda environment, configuration files, and a Makefile. A Conda environment keeps the project's Python packages separate from other projects.

In plain words
What is it for?
Starting Python, machine-learning, research, or other experiment projects.
Why use it?
It removes the repeated setup work and gives new projects a consistent starting structure.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

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 skills/neha2110/brainstorming-buddy-template/scaffold-python-experiment
Any agent
npx skills add neha2110/brainstorming-buddy-template --skill scaffold-python-experiment
Clone the repo
git clone --depth 1 https://github.com/neha2110/brainstorming-buddy-template

Made for: Claude Code, Codex.

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 scaffold-python-experiment

README.md
[![agentmods](https://agentmods.dev/badge/skills/neha2110/brainstorming-buddy-template/scaffold-python-experiment.svg)](https://agentmods.dev/skills/neha2110/brainstorming-buddy-template/scaffold-python-experiment)
Your own site
<a href="https://agentmods.dev/skills/neha2110/brainstorming-buddy-template/scaffold-python-experiment"><img src="https://agentmods.dev/badge/skills/neha2110/brainstorming-buddy-template/scaffold-python-experiment.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,016 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. Scan, not verified.
Origin unknown 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 $0.00067 $0.01016
Opus 5 $0.00034 $0.00508
Sonnet 5 $0.00013 $0.00203
Haiku 4.5 $0.00007 $0.00102

Measured 5d ago against content hash d6d8217fff55, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade C, and why

scaffold-python-experiment scanned grade C with 1 finding 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 5d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

rm -rf results/*
skills/scaffold-python-experiment/SKILL.md · 190 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 5d ago First seen · 190 lines · 67 tokens per session scan C d6d8217fff55

Subscribe to this mod's changes

scaffold-python-experiment is a skill published in the GitHub repository neha2110/brainstorming-buddy-template (2 stars, last pushed 4mo ago), with no licence file. It adds 67 tokens to every session and 1,016 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

jupyter-notebook

Iterative Python via live Jupyter kernel (hamelnb).

NousResearch/hermes-agent · 18 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use…

K-Dense-AI/scientific-agent-skills · 73 tokens

pennylane

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…

K-Dense-AI/scientific-agent-skills · 98 tokens

biology-biopython

Bioinformatics with Biopython for sequence manipulation, file parsing, BLAST, and phylogenetics. Use when working with DNA/RNA/protein sequences or biological databases.

aiming-lab/AutoResearchClaw · 40 tokens

cuopt-numerical-optimization-api

LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.

NVIDIA/skills · 51 tokens