Borrowing it
Nothing to install: this file belongs to Dangooy/trade-pipeline-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Dangooy/trade-pipeline-skill/main/.claude/skills/trade-pipeline-init/SKILL.mdgit clone --depth 1 https://github.com/Dangooy/trade-pipeline-skillWrote 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/dangooy/trade-pipeline-skill/trade-pipeline-init)<a href="https://agentmods.dev/skills/dangooy/trade-pipeline-skill/trade-pipeline-init"><img src="https://agentmods.dev/badge/skills/dangooy/trade-pipeline-skill/trade-pipeline-init/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/dangooy/trade-pipeline-skill/trade-pipeline-init"><img src="https://agentmods.dev/badge/skills/dangooy/trade-pipeline-skill/trade-pipeline-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00015 | $0.01232 |
| Opus 5 | $0.00008 | $0.00616 |
| Sonnet 5 | $0.00003 | $0.00246 |
| Haiku 4.5 | $0.00002 | $0.00123 |
Grade A, and why
trade-pipeline-init 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 11d 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Pipeline Init — Interactive Setup Skill
Trigger
When the user says "初始化配置", "setup", "configure trade pipeline", "init", "第一次使用", or when trade_pipeline/config/config.yaml contains example/placeholder data (seller name is "ACME EXPORT").
Behavior
Use AskUserQuestion to guide the user through configuring their trade pipeline. Collect all information first, then write config.yaml in one step.
Step 1: Company Info
Ask with AskUserQuestion (multiSelect: false):
- "你的公司英文名?" — free text input (user selects "Other")
Then ask:
- "公司中文名(可选)?"
- "公司地址?"
- "联系人姓名?"
- "联系邮箱?"
- "联系电话?"
These can be combined into 2-3 rounds of AskUserQuestion, grouping related fields.
Step 2: Trade Terms
Ask with AskUserQuestion options:
question: "默认贸易条件?"
options:
- label: "FOB"
description: "Free On Board — 卖方交到港口,买方负责运输"
- label: "CIF"
description: "Cost, Insurance, Freight — 卖方负责运费+保险到目的港"
- label: "DDP"
description: "Delivered Duty Paid — 卖方全包到买方门口"
- label: "EXW"
description: "Ex Works — 买方自提"
Step 3: Currency & Port
Ask with AskUserQuestion options:
question: "默认币种?"
options:
- label: "USD"
- label: "CNY"
- label: "EUR"
question: "默认装运港?"
options:
- label: "QINGDAO,CHINA"
- label: "SHANGHAI,CHINA"
- label: "NINGBO,CHINA"
Step 4: Payment & Lead Time
Ask:
- "付款条件?" (default: "30% T/T deposit; 70% before shipment")
- "交货期?" (default: "45-60 days after deposit")
Step 5: First Buyer (Optional)
Ask:
question: "现在添加第一个客户吗?"
options:
- label: "是,添加客户"
- label: "跳过,稍后再加"
If yes, ask buyer name, address, contact, email.
Step 6: Write Config
After collecting all info, generate the YAML config and write to:
trade_pipeline/config/config.yaml
Use the following structure:
sellers:
<seller_id>:
name_cn: <中文名>
name_en: <英文名>
address: <地址>
contact: <联系人>
tel: <电话>
email: <邮箱>
bank: { name: "", swift: "", account_no: "" }
buyers:
<buyer_id>: # if provided
name_en: <名称>
legal_names: [<名称>]
aliases: [<简称>]
address: <地址>
contact: <联系人>
email: <邮箱>
format_defaults:
standard:
seller_id: <seller_id>
currency: <币种>
price_unit: "<币种>/PC"
terms_id: "default_<币种小写>"
terms_templates:
default_<币种小写>:
payment: <付款条件>
delivery: "<贸易条件> <装运港>, Incoterms 2020."
lead_time: <交货期>
validity: "10 days"
packing: "Standard export packaging: 25 kg cartons, Euro pallets."
quality: "100% inspection before shipment."
defaults:
port_of_loading: <装运港>
pi_number_pattern: "PI-{order_no}"
ci_number_pattern: "CI-{order_no}"
quote_no_pattern: "QT-{order_no}"
date_format: "%d %B %Y"
packing:
carton_weight_kg: 25
pallet_self_weight_kg: 28
cartons_per_pallet: 36
pl_profiles:
default:
pl_config: standard
packing_profile: standard_25kg
cache:
dir: .cache/understanding
prompt_version: v1.0
schema_version: v1.0
enabled: true
ocr_review:
force_review_fields: [description, standard, quantity, unit, weight_kg]
confidence_threshold: 0.90
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.
- 11d ago First seen · 178 lines · 15 tokens per session scan A 4e4781d2d698
trade-pipeline-init is a skill published in the GitHub repository Dangooy/trade-pipeline-skill (25 stars, last pushed 6d ago), licensed MIT. It adds 15 tokens to every session and 1,232 once invoked, about $0.0001 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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