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.
npx skills add ChenyCHENYU/wl-skills-design --skill requirements-flowchartgit clone --depth 1 https://github.com/ChenyCHENYU/wl-skills-designWrote 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/skills/chenychenyu/wl-skills-design/requirements-flowchart)<a href="https://agentmods.dev/skills/chenychenyu/wl-skills-design/requirements-flowchart"><img src="https://agentmods.dev/badge/skills/chenychenyu/wl-skills-design/requirements-flowchart/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/skills/chenychenyu/wl-skills-design/requirements-flowchart"><img src="https://agentmods.dev/badge/skills/chenychenyu/wl-skills-design/requirements-flowchart.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 | $0.00067 | $0.00530 |
| Opus 5 | $0.00034 | $0.00265 |
| Sonnet 5 | $0.00013 | $0.00106 |
| Haiku 4.5 | $0.00007 | $0.00053 |
Grade A, and why
requirements-flowchart 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 10d 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.
What it actually says
业务流程图
先确定模式
create：生成流程图，并仅对本轮新产物执行修复闭环。validate：只读检查现有文件，未经明确授权不得修改。review：与validate相同，只读给出评审结论，不默认保存报告。repair：用户明确要求后，先给出问题和差异，再修改并复验。
至少确认流程名称或目标。角色、范围、起止条件和节点可从上下文推断；无法推断时只追问最关键的一项。
执行流程
- 读取唯一规则源：流程图标准。
- 新建文件时读取 draw.io 骨架；需要版式参考时读取 匿名样例说明。
- 使用标准活动编码
[流程编码]-[操作类型]-[NN]，例如ORD-A-01-E-01。 - 生成可被 draw.io 打开的 XML，不得只输出 Mermaid、ASCII 或图片。
- 执行标准第十五章 20 项验证：先运行
wl-skills-design verify flowchart --file {产物路径}获取 [M] 项机械结论（CLI 不可用时由 Agent 代执行），再判 [J] 项；缺少 spec 时将 FC-01～FC-05 标为Pending，不得伪造通过。 - 检查 XML 可解析、ID 唯一、引用存在、连接线落在节点上，并尽可能完成渲染检查。
交付约束
- 默认写入
docs/flowchart/{流程编码}-{流程名称}.drawio。 - 报告逐项给出规则 ID、结果、证据位置和建议。
- 创建模式可修复本轮生成文件；验证模式只报告，除非用户明确要求修复。
- 最终说明 Skill、标准、产物路径、20 项结果和 Pending 项。
What ships with it
3 files 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.
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.
- 10d ago First seen · 32 lines · 67 tokens per session scan A b2632f5403d9
requirements-flowchart is a skill published in the GitHub repository ChenyCHENYU/wl-skills-design (5 stars, last pushed 26d ago), licensed Apache-2.0. It adds 67 tokens to every session and 530 once invoked, about $0.0003 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…