Agent skill

Tw Ecom Dtc Shopline

by asgard-ai-platform in asgard-ai-platform/skills

Integrate and operate Shopline in Taiwan e-commerce context via mcp-shopline.

MITAuto-check passedSales & Support

Install Tw Ecom Dtc Shopline

skills CLI
$ npx skills add asgard-ai-platform/skills --skill tw-ecom-dtc-shopline -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install asgard-ai-platform/skills tw-ecom-dtc-shopline --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tw-ecom-dtc-shopline .claude/skills/tw-ecom-dtc-shopline && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tw-ecom-dtc-shopline
GitHub stars
242
Token cost
~2.8k tokens
SKILL.md length
979 words
Files
3 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Integrate and operate Shopline in Taiwan e-commerce context via mcp-shopline.

  • The user needs to sync orders
  • SKILL.md covers When to use this skill, Do NOT use when, Core concepts and Decision tree, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Manage products

What it does

Tw Ecom Dtc Shopline is an agent skill from asgard-ai-platform/skills. Integrate and operate Shopline in Taiwan e-commerce context via mcp-shopline. Use when the user needs to sync orders, manage products, run promotions, or reconcile inventory on Shopline stores; when comparing Shopline vs 91APP/Shopify for Taiwan DTC; or when debugging async write propagation. Do NOT use for API schema lookup (go to mcp-shopline docs) or non-Taiwan Shopline deployments.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `examples/sample_scenario.md` and `references/tool-catalog.md`).

It sits in Sales & Support, covering OpenAPI specifications, Deployment and E-commerce operations. It works with Model Context Protocol and Shopify. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user needs to sync orders
  • Manage products
  • Reconcile inventory on Shopline stores
  • Comparing Shopline vs 91APP/Shopify for Taiwan DTC

Example prompts

  • “/tw-ecom-dtc-shopline”

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tw Ecom Dtc Shopline loads about 2.8k tokens when it runs, and up to ~4.7k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 979 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~102
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 979 words, ~2,794 tokens.

Download SKILL.mdSave it as .claude/skills/tw-ecom-dtc-shopline/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
tw-ecom-dtc-shopline
description
Integrate and operate Shopline in Taiwan e-commerce context via mcp-shopline. Use when the user needs to sync orders, manage products, run promotions, or reconcile inventory on Shopline stores; when comparing Shopline vs 91APP/Shopify for Taiwan DTC; or when debugging async write propagation. Do NOT use for API schema lookup (go to mcp-shopline docs) or non-Taiwan Shopline deployments.
metadata.category
WP-01 電商
metadata.domain
ecommerce-tw
metadata.layer
platform
metadata.related_mcps
mcp-shopline
metadata.related_skills
tw-ecom-channel-strategy, tw-ecom-invoice-ezpay, tw-ecom-payment-newebpay, ecom-rfm-analysis, ecom-promo-roi, ecom-inventory-health
metadata.last_verified
2026-04
metadata.tags
taiwan, e-commerce, shopline, platform, integration

Shopline Integration Methodology

When to use this skill

  • Syncing orders, products, members, or inventory between Shopline and an internal ERP / data warehouse
  • Building a multi-step automation across mcp-shopline tools (e.g., order → invoice → logistics)
  • Reconciling Shopline state against an external system (accounting, WMS, 電子發票 平台)
  • Designing a promotion / coupon / flash-sale workflow that spans read + write tools
  • Debugging unexpected behavior: missing orders, stale reads after writes, 403 on channel lookups

Do NOT use when

  • You need the exact API schema for one endpoint — read the tool description or Shopline Open API docs directly
  • The merchant is on Shopify, 91APP, Cyberbiz, or a non-Shopline platform — use tw-ecom-channel-strategy first
  • The Shopline store is non-Taiwan (HK/SG/MY) — currency, invoice, and logistics assumptions in this skill are TWD + Taiwan-specific

Core concepts

Shopline is a SaaS commerce platform popular with Taiwan DTC and omnichannel brands. A single merchant account can own multiple shops (storefronts); each shop can sell through multiple channels (online + POS retail stores). mcp-shopline wraps Shopline Open API v1 into 143 tools (75 read, 68 write), all scoped to one API token = one merchant context.

Two axes matter when picking a tool:

  • Read vs write. Write tools are prefixed [WRITE] in their descriptions and require an API token scope that permits mutation. Read tools are safe; write tools modify production data.
  • Domain. Orders, Products & Inventory, Analytics, Customers, Categories & Promotions, Order Extended (returns/delivery/conversations/reviews), Store Settings. Analytics tools are pre-aggregated — prefer them over hand-rolling aggregations on top of query_orders.

Money is always TWD float. Dates are YYYY-MM-DD strings. Online orders use status confirmed; POS orders use completed — mixing them up silently drops half the data.

Decision tree

What is the user asking for?
│
├─ Aggregate metric (revenue, AOV, top products, trend)?
│    → Analytics / Orders summary tools
│      get_sales_summary · get_top_products · get_sales_trend
│      get_channel_comparison · get_rfm_analysis · get_promotion_roi
│
├─ Specific order / customer / product lookup?
│    → Read-detail tools
│      get_order_detail · get_customer_profile · get_product_variants
│
├─ Inventory question (stock, low-stock, warehouse)?
│    → Products & Inventory read tools
│      get_inventory_overview · get_low_stock_alerts ·
│      get_stock_by_warehouse · get_locked_inventory
│
├─ Promotion / coupon / flash sale?
│    ├─ Read  → list_promotions · get_promotion_detail ·
│    │          list_flash_price_campaigns · list_affiliate_campaigns
│    └─ Write → promotion write tools (12) — split into three sub-families:
│              flat promo · flash price · gift/add-on. See
│              references/tool-catalog.md for exact tool per family.
│
├─ Modify an order (status, tag, fulfill, cancel)?
│    → Order write tools (8) — require write scope
│
├─ Create/update customer, adjust store credits, group membership?
│    → Customer write tools (6)
│
└─ Configuration / debug (token scope, channels, payments, delivery)?
     → Store Settings read tools
       get_token_info (always start here when debugging permissions)
       list_channels · list_payments · list_delivery_options

Implementation guidance

Common multi-tool flows. For each, use the tool names below; see examples/sample_scenario.md for an end-to-end walkthrough.

Order sync (Shopline → internal ERP)

  • Poll with query_orders on a date window; include BOTH confirmed (online) and completed (POS) statuses
  • For each order, call get_order_detail for line items and get_order_transactions for payment records
  • If delivery matters, call get_order_delivery — note: delivery has its own ID, only available after shipment executes
  • Persist the order.channel.created_by_channel_name value, not just created_from, or you lose the physical store identity
  • Checkpoint the high-water-mark date to avoid re-fetching; re-scan the last 24-48h each run to catch late status changes

Promotion setup and measurement

  • Pre-check: list_promotions + search_promotions to avoid duplicate campaign names
  • Create via the promotion write tool appropriate to type (flat promotion vs flash price vs gift-with-purchase vs add-on)
  • After go-live, measure with get_promotion_analysis (effectiveness) + get_promotion_roi (lift vs baseline)
  • For affiliate campaigns, use get_affiliate_campaign_usage — requires at least one order that used the campaign

Member / RFM sync

  • Full membership sync: list_customers (paginated) → for each, get_customer_profile on demand (not in bulk — expensive)
  • Segmentation: call get_rfm_analysis instead of computing from raw orders — it's pre-aggregated and respects Shopline's definition of a member
  • For tier / points state: list_membership_tiers, list_member_point_rules, list_store_credits
  • get_customer_lifecycle compares two periods' RFM to surface upgrades and churn

Inventory sync and replenishment

  • Snapshot: get_inventory_overview (totals) + get_stock_by_warehouse (per-warehouse matrix)
  • Operational signals: get_low_stock_alerts, get_locked_inventory (reserved by pending orders), get_slow_movers (excess stock)
  • Transfer planning: get_stock_transfer_suggestions — server-side heuristic; treat output as suggestions not commands
  • Replenishment: list_purchase_orders → get_purchase_order_detail; create via purchase-order write tools
Show full SKILL.md (465 more words)Show less

Gotchas

  • Order status split by channel — confirmed vs completed. Online orders use confirmed; POS uses completed. The tools include both by default, but if you pass a custom status filter and forget one, you silently lose half the data. Always verify with get_channel_comparison that online and POS counts look plausible.
  • Pagination caps. per_page maxes at 50, and search returns are capped at 10,000 results total. For large windows, split the date range (Shopline Open API uses fetch_all_pages_by_date_segments internally, but your own multi-step flows need the same discipline). A 30-day top-seller query on a high-volume merchant will hit the cap.
  • Async write propagation — read-after-write can be stale. After calling a [WRITE] tool (e.g., update_order_status, adjust_store_credit), an immediate read may still return the pre-write state. Do not gate downstream logic on a read-after-write within the same sync step. Build a reconciliation loop, or pass the write response's own updated_at forward. (TODO: verify exact propagation window with Shopline Open API support or mcp-shopline maintainers.)
  • No webhook support yet (as of 2026-04). mcp-shopline roadmap lists webhooks as pending. Until then, all event detection is polling. Budget API calls accordingly and pick a poll cadence (5-15 min for orders, hourly for inventory) that respects the 0.2s inter-page delay the tools enforce.
  • Channels endpoint often 403/422; fall back to order payload. list_channels / get_channel_detail require a separate permission that most tokens don't carry. The same information (store name, channel type) is available via order.channel.created_by_channel_name on any order detail — use that as the authoritative source when channel tools fail.
  • Write tools need explicit scope AND SHOPLINE_TEST_WRITES=1 in tests. Tokens default to read-only scope; production write failures usually mean the scope wasn't granted, not that the tool is broken. Start debugging with get_token_info to confirm scope before assuming a bug. In test harnesses, writes are gated behind the env var — unset it in CI unless you have a dedicated test store.

IRON LAW

Never filter orders on status or created_from alone. Online orders use confirmed, POS uses completed, and the store identity lives on order.channel.created_by_channel_name — not on created_from ("shop" / "pos"). Any order query that hard-codes one status or keys off created_from will silently drop POS revenue, misattribute store sales, or both. Always pass both statuses (or omit the filter) and always carry the channel name forward in downstream records.

Rationalization Table
"但是…"為什麼錯
我只需要線上訂單,status=confirmed 就夠了POS 訂單用 completed,hard-code confirmed 會靜默丟失所有實體門市營收
created_from 欄位明確標示 "shop" vs "pos",用它來分類就好created_from 不是通路身份的權威來源;門市名稱只在 order.channel.created_by_channel_name 中,跨店分析時用 created_from 會錯誤合併所有實體店
只拿 confirmed 是效能最佳化,不是資料遺失範圍縮小不等於最佳化;用日期區間分頁才是正確的效能手段,不是靠省略 POS 訂單
這個報表只給線上部門,POS 不在範圍內商業邏輯範圍不等於查詢範圍;即使報表只看線上,下游 ERP 或發票系統仍可能吃到這份 query 結果

Output Format

When completing a Shopline task, produce this structure:

markdown
# Shopline Task: {one-line summary}

## Context
- Merchant / shop: {name} (single-merchant token assumed)
- Scope of work: {read-only analysis | sync | write mutation | full integration}
- Date window / entity scope: {…}

## Tool Plan
| Step | Tool | Read/Write | Purpose |
|------|------|-----------|---------|
| 1 | get_token_info | R | Confirm scope covers the tools below |
| 2 | {tool} | R/W | {…} |
| … | … | … | … |

## Assumptions & Open Questions
- {assumption grounded in a Shopline constraint}
- TODO: {anything that needs verification against mcp-shopline or Open API docs}

## Execution Notes
- Both `confirmed` and `completed` statuses included: Y/N
- Channel name carried forward from `order.channel.created_by_channel_name`: Y/N
- Pagination strategy (date segmentation if >10k results): {…}
- Read-after-write handling (reconciliation loop, not immediate re-read): {…}

## Deliverable
{the actual answer, dataset, or change summary}
  • MCPs: mcp-shopline
  • Skills: tw-ecom-channel-strategy (Shopline vs 91APP/Shopify decision), tw-ecom-invoice-ezpay (e-invoice handoff), tw-ecom-payment-newebpay (payment reconciliation), ecom-rfm-analysis (segmentation methodology), ecom-promo-roi (lift measurement), ecom-inventory-health (stock KPIs)
  • References: references/tool-catalog.md (one-line per tool, grouped by domain), examples/sample_scenario.md (end-to-end order → invoice flow)

Last verified: 2026-04

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in tw-ecom-dtc-shopline of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/tool-catalog.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Tw Ecom Dtc Shopline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tw Ecom Dtc Shopline compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tw Ecom Dtc Shopline this skillasgard-ai-platform/skills242—~2.8kAutomated safety check: PassMIT
Shopifyasgeirtj/system_prompts_leaks69k—~2kAutomated safety check: PassCC0-1.0
CloudbaseLeoYeAI/openclaw-master-skills2.2k1 repos~4.7kAutomated safety check: PassMIT
Zach Sif Cvr Threshold Analyzerzach22-1999/amazon-skills2091 repos~982Automated safety check: NotesMIT
Checkout Purchasekeypo-us/keypo-cli182—~880Automated safety check: NotesNone
Hostinger Headless Entryhostinger/api-mcp-server160—~1.3kAutomated safety check: PassMIT

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Questions about Tw Ecom Dtc Shopline

What does Tw Ecom Dtc Shopline do?

Integrate and operate Shopline in Taiwan e-commerce context via mcp-shopline. Tw Ecom Dtc Shopline is an agent skill from asgard-ai-platform/skills. Integrate and operate Shopline in Taiwan e-commerce context via mcp-shopline.

When should I use Tw Ecom Dtc Shopline?

Tw Ecom Dtc Shopline fits situations like: the user needs to sync orders; manage products; reconcile inventory on Shopline stores; comparing Shopline vs 91APP/Shopify for Taiwan DTC.

How do I install Tw Ecom Dtc Shopline in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill tw-ecom-dtc-shopline -a claude-code`. Or copy the skill folder (tw-ecom-dtc-shopline in asgard-ai-platform/skills) into .claude/skills/tw-ecom-dtc-shopline in your project. Claude Code loads it when a task matches its description.

How do I install Tw Ecom Dtc Shopline in Codex?

Run `npx skills add asgard-ai-platform/skills --skill tw-ecom-dtc-shopline -a codex`. Or copy the skill folder (tw-ecom-dtc-shopline in asgard-ai-platform/skills) into .agents/skills/tw-ecom-dtc-shopline in your project. Codex loads it when a task matches its description.

Can I use Tw Ecom Dtc Shopline in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill tw-ecom-dtc-shopline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tw-ecom-dtc-shopline, .gemini/skills/tw-ecom-dtc-shopline, .github/skills/tw-ecom-dtc-shopline and .opencode/skills/tw-ecom-dtc-shopline in your project.

What does Tw Ecom Dtc Shopline need to run?

SKILL.md names no scripts, command-line tools or credentials: Tw Ecom Dtc Shopline is instructions for the agent only.

Does Tw Ecom Dtc Shopline access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tw Ecom Dtc Shopline safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tw Ecom Dtc Shopline use?

Tw Ecom Dtc Shopline is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tw Ecom Dtc Shopline use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Tw Ecom Dtc Shopline?

Skills that share tags, products or a category with Tw Ecom Dtc Shopline: Shopify (asgeirtj/system_prompts_leaks, 69k stars), Cloudbase (LeoYeAI/openclaw-master-skills, 2.2k stars), Zach Sif Cvr Threshold Analyzer (zach22-1999/amazon-skills, 209 stars) and Checkout Purchase (keypo-us/keypo-cli, 182 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tw Ecom Dtc Shopline?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.