group_by_name

A file-organising tool that groups files into folders according to rules in their names.

In plain words
What is it for?
Sorting files into directories by name and optionally choosing a separate output directory. Its behaviour is marked as needing testing.
Why use it?
It reduces manual sorting when filenames share prefixes or other consistent patterns.

Skill for Claude CodeCodex

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/coderwanfeng/python-office/group_by_name
Any agent
npx skills add CoderWanFeng/python-office --skill group_by_name
Clone the repo
git clone --depth 1 https://github.com/CoderWanFeng/python-office

Made for: Claude Code, Codex.

Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 256 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00036 $0.00256
Opus 5 $0.00018 $0.00128
Sonnet 5 $0.00007 $0.00051
Haiku 4.5 $0.00004 $0.00026

Measured yesterday against content hash 2bd9909f5f86, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

group_by_name 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.

The scan reads SKILL.md. This mod also ships 1 executable file (__init__.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/file/group_by_name/SKILL.md · 47 lines

What it actually says

group_by_name Skill

按名称分组整理文件

功能描述

按文件名的前缀或规则,将文件分组整理到不同目录中。

⚠️ TODO: 该功能为历史功能,行为待测试。

所属分类

office/skills/file/group_by_name/

调用方式

from skills.file import group_by_name

group_by_name(
    path='./data',
    output_path=None,
    del_old_file=None
)

参数说明

参数 类型 必填 默认值 说明
path str - 路径
output_path str None 输出路径
del_old_file bool None 是否删除旧文件

返回值

None

原始函数

office.api.file.group_by_name

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. yesterday First seen · 47 lines · 36 tokens per session scan A 2bd9909f5f86

Subscribe to this mod's changes

group_by_name is a skill published in the GitHub repository CoderWanFeng/python-office (1,346 stars, last pushed 12d ago), licensed Apache-2.0. It adds 36 tokens to every session and 256 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 2026-08-30.

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