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 medalsoftchina/workcopilot --skill doa-quotationgit clone --depth 1 https://github.com/medalsoftchina/workcopilotWrote 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/medalsoftchina/workcopilot/doa-quotation)<a href="https://agentmods.dev/skills/medalsoftchina/workcopilot/doa-quotation"><img src="https://agentmods.dev/badge/skills/medalsoftchina/workcopilot/doa-quotation/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/medalsoftchina/workcopilot/doa-quotation"><img src="https://agentmods.dev/badge/skills/medalsoftchina/workcopilot/doa-quotation.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 | $0.00228 | $0.06077 |
| Opus 5.5 | $0.00091 | $0.02431 |
| Sonnet 5.5 | $0.00046 | $0.01215 |
| Haiku 4.5 | $0.00023 | $0.00608 |
Grade A, and why
doa-quotation 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 566 lines — stays where its author put it; the contents beside it link to each section on GitHub.
报价与敏捷任务拆分生成
工作流概览
用户提供需求/客户/项目信息
→ 确认输出模式（经典报价 / 敏捷方式）
→ 搜索并比对当前工作区模板
→ 结构化整理报价项或 Sprint/任务项
→ 生成 Excel 或 Python 生成脚本
→ 校验工时/金额/税率/样式
→ 输出最终文件路径与说明
何时使用
- 用户说“帮我做报价”“生成报价单”“整理工时报价”
- 用户说“按敏捷方式拆任务”“做 Sprint 拆分”“生成敏捷排期 Excel”
- 用户提供客户名称、项目名称，希望参考已有模板生成新的 Excel
- 用户提供 Python/openpyxl 脚本或历史 Excel，要求按同类风格生成新版本
Step 0: 必须先确认输出模式
当用户只说“做报价”或“做任务拆分”，必须先使用 vscode_askQuestions 确认：
- 经典报价
- 适合固定范围、按模块/工时/费用输出传统报价单
- 敏捷方式
- 适合按 Sprint、任务、人天、验收标准输出敏捷任务拆分表
推荐问题：
问题：本次希望采用哪种输出方式？
选项：
- 经典报价 ← recommended
- 敏捷方式（Sprint / 任务拆分）
如果用户已经明确说了“经典报价”或“敏捷方式”，可以跳过这一步。
Step 0.5: 必须确认期望总工时范围
在进入模板选择和任务拆分前，必须再使用 vscode_askQuestions 确认期望的总工时范围，单位为人天。
推荐问题：
问题：本次期望的总工时范围是？
选项：
- 10人天以下
- 10-30人天
- 30-50人天
- 50-70人天 ← recommended
- 70-100人天
使用规则：
- 这个范围是生成报价和任务拆分时的重要约束，不应跳过
- 若用户已明确给出目标工时或目标预算可推导工时范围，可直接采用并在最终说明中写明
- 若用户选择的工时范围与参考模板差距很大，应优先调整任务粒度、Sprint 数量或模块范围，而不是机械照搬模板
- 经典报价与敏捷方式都应记录该范围，作为总人天校验依据
Step 1: 收集最小必要信息
至少确认以下信息；如用户未提供，继续追问缺失项：
- 客户名称
- 项目名称
- 需求描述或范围说明
- 输出模式
- 期望总工时范围
- 人天单价（必填，单位：元/人天，例如 2200、3000、3500）
- 是否有参考模板
人天单价必须由用户提供，不使用任何默认值。如果用户未主动给出，使用
vscode_askQuestions追问。
建议补充信息：
- 报价主体
- 默认：用户公司名称（需用户提供）
- 税率
- 默认沿用模板；无模板时单独确认
- 交付周期
- 角色与单价口径
- 例如 PM/BA 与 PG/PT 是否同价，SA、QA 是否有独立单价
- 是否需要同时输出 Python 生成脚本
Step 2: 先找模板，再决定结构
优先在当前工作区搜索并复用现有模板，而不是从零随意生成。
模板搜索优先级
- 同客户、同项目族的 Excel 或 Python 生成脚本
- 同类型文档模板
- 报价单、敏捷任务拆分、Sprint 计划、工时校验
- 用户本次显式提供的附件或脚本
- 如果仍然没有，再基于通用结构新建
客户名称自动匹配规则
在搜索模板前，优先根据客户名称锁定候选目录，再在目录内按输出模式挑选模板。
当前工作区已知映射
以下为示例映射，实际使用时根据工作区中的客户目录自动发现。
- 客户名称包含：
示例客户、ExampleCorp- 优先目录：
ExampleCorp/ - 经典报价优先模板：
ExampleCorp/示例项目.工时报价.xlsx
- 敏捷拆分优先模板：
ExampleCorp/示例项目_敏捷任务拆分.xlsx
- Python 参考脚本：
ExampleCorp/示例项目_敏捷任务拆分.py
- 优先目录：
匹配流程
- 先读取用户输入中的客户名称
- 如果客户名称命中已知映射，先限定到对应目录搜索
- 在对应目录中按输出模式筛选：
- 经典报价：优先
报价、工时报价、quotation - 敏捷方式：优先
敏捷任务拆分、Sprint、工时校验
- 经典报价：优先
- 如果同目录存在多个候选模板：
- 优先用户显式提到的项目名
- 其次优先最新日期版本
- 再其次优先已有配套 Python 脚本的模板族
- 如果客户名称未命中任何已知映射，再退回通用搜索策略
What ships with it
4 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.
- 1mo ago First seen · 566 lines · 228 tokens per session scan A c77c6c7d623f
doa-quotation is a skill published in the GitHub repository medalsoftchina/workcopilot (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 228 tokens to every session and 6,077 once invoked, about $0.0009 per session on Opus 5.5. 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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