apparel-brand

apparel-brand is a skill for Claude Code, Codex from text2future/flowix. It costs 29 tokens per session (707 once invoked), scanned A, a copy of ai-assistant, MIT.

A documented workflow for developing a clothing brand and its product lines, from defining the audience and style through fitting samples, production, listing, and sales review. It records decisions about materials, measurements, sizes, and costs.

In plain words
What is it for?
Use it to plan clothing styles, record sample fittings and alterations, confirm production details, prepare listings, and review returns caused by fit, quality, or customer preference.
Why use it?
It keeps design changes and fitting results tied to the version that is produced and sold. It also separates stock and returns by style and size, making problems easier to identify.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

Good fit Use it to plan clothing styles, record sample fittings and alterations, confirm production details, prepare listings, and review returns caused by fit, quality, or customer preference.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/text2future/flowix/apparel-brand
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.

Any agent
npx skills add text2future/flowix --skill apparel-brand
Clone the repo
git clone --depth 1 https://github.com/text2future/flowix

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 apparel-brand

README.md
[![agentmods](https://agentmods.dev/badge/skills/text2future/flowix/apparel-brand/github.svg)](https://agentmods.dev/skills/text2future/flowix/apparel-brand)
Your own site
<a href="https://agentmods.dev/skills/text2future/flowix/apparel-brand"><img src="https://agentmods.dev/badge/skills/text2future/flowix/apparel-brand/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.

agentmods 80×15 button for apparel-brand

Your own site · 80×15
<a href="https://agentmods.dev/skills/text2future/flowix/apparel-brand"><img src="https://agentmods.dev/badge/skills/text2future/flowix/apparel-brand.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 707 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 81% copy Near-identical to another mod 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 $0.00029 $0.00707
Opus 5.5 $0.00012 $0.00283
Sonnet 5.5 $0.00006 $0.00141
Haiku 4.5 $0.00003 $0.00071

Measured 7d ago against content hash 97dabf085b74, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

apparel-brand 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 7d 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.

Origin

This is a copy

81% identical to ai-assistant — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.flowix/templates/notebook-templates/服饰品牌/.agents/skills/apparel-brand/SKILL.md · 34 lines

What it actually says

先读主题根目录 AGENTS.md、公共/项目启动书.md 和 公共/品牌与系列企划.md。所有路径相对主题根目录。

推进本主题

本主题流程:品牌定位 → 系列设计 → 打样试穿 → 生产上架 → 销售复盘。

  1. 品牌定位:明确客群、场景和系列风格边界。
  2. 系列设计:确认款式、面料、结构与尺码要求。
  3. 打样试穿:打样后试穿,记录修改尺寸和重新确认结果。
  4. 生产上架:按确认版本生产与验货,分款式尺码上架。
  5. 销售复盘:分款式尺码统计库存和退货,区分版型、质量与偏好问题。
  • 任务入口:进度视图.csv。按事项ID查找记录,展示给用户时使用任务名称。
  • 决策与依据:系列/计划表.csv、系列/资料/资料清单.csv。
  • 新任务:复制 公共/款式开发单.md,在 款式/ 下用可读的任务名称建目录;场次、批次等重复任务加日期。
  • 填写案例与真实任务时沿用空白模板的标题和字段,不另造一套简化结构。字段不适用写明原因;资料缺失时说明缺口及影响。过程写已发生的动作,产物保存到任务目录并登记实际路径。
  • 结果写入 数据/款式销售.csv,沿用同一事项ID。检查字段单位、时间范围和对象粒度;单次任务不填项目累计数。缺失值不得用0代替。
  • 本主题完成条件:版型、面料、尺码与成本确认。先逐项核对模板中的审核字段,再更新状态;缺少影响验收的证据时保持待确认。

本库中的教学记录

款式/直筒衬衫款式/任务记录.md 与 款式/直筒衬衫款式/直筒衬衫M码试售.md 展示一次任务的记录及产物。其中人物和数据为模拟;未经用户要求,不把模拟数据当作真实事实或继续虚构实际结果。外部发布、支付和联系按用户授权执行。

数据记录先确认一行代表什么对象、哪段时间与什么单位。原始记录、分类合计和项目汇总分别维护;验收表的期望结果必须与实际结果逐项对应,不能只填写“通过”。

接续任务

第二项教学任务为 款式/直筒衬衫M码第二周试售/任务记录.md。从前序反馈提取下一步,先建立新ID与计划行,再填写同一公共模板;复用数据不重复登记。更新视图前核对产物存在、审核结论与状态一致。

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. 7d ago First seen · 34 lines · 29 tokens per session scan A 97dabf085b74

Subscribe to this mod's changes

apparel-brand is a skill published in the GitHub repository text2future/flowix (469 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 707 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 81% identical to ai-assistant, differing in 30 lines, and is treated as a copy.

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