Sourcing Selection

Follow shared release-shell rules in:

• postplus-shared release-shell rules

Use this skill when the user is not just asking for platform data, but for a real sourcing or product-selection judgment.

Typical requests:

• 这个产品值不值得找货源
• 适合先上 Amazon 还是 TikTok Shop
• 1688 上有货，但有没有需求侧证据支撑
• 帮我把供给侧和需求侧拼起来做判断
• 给我一个更接近真实决策的找货源结论

This skill is an orchestration and synthesis layer.

It should not replace platform skills. It should decide which evidence to collect, in what order, and how much judgment is justified.

Read first:

• postplus-shared product-selection preferences

Design Goal

Keep the current version simple, but make the interface extensible.

The skill should think in capability groups, not hard-coded platforms:

• supply-side source
• search-intent source
• demand-side source
• content-language source
• finance layer
• compliance layer

Today, these groups may map to:

• 1688 for supply-side
• Google Trends for search-intent
• Amazon for search-led demand
• TikTok Shop for marketplace demand
• TikTok for content and audience language

In the future, the same groups may map to:

• Alibaba, Made-in-China, GlobalSources, Temu supplier-side, offline vendor lists
• Google Trends, Baidu Index, ad-library, search-console-like, Shopee, Etsy, Temu, independent-site

Do not write the skill as if 1688 + Amazon + TikTok Shop are permanent.

Core Rule

A sourcing judgment is only as strong as its weakest missing layer.

Always separate:

• Observed from evidence
• Inference
• Missing layer

If the user asks for a yes/no decision and the evidence is incomplete, return:

• the provisional judgment
• what supports it
• what is still missing

Do not fake certainty.

Minimal Decision Model

Use this order unless the user explicitly asks otherwise:

1. demand proof
2. competition shape
3. channel fit
4. merchant-model fit
5. supply-side feasibility
6. unit-economics pressure
7. compliance or operational risk

This is intentionally simple. Do not turn it into a giant scorecard unless the user asks.

Input Shapes

Classify the request first:

1. Product Idea Validation

Use when the user asks:

• 这个产品值不值得做
• 这个方向能不能找货源来卖

Default route:

1. collect demand-side proof
2. collect supply-side feasibility
3. synthesize

2. Supply-Led Opportunity Check

Use when the user already has a supply-side signal:

• 1688 上看到很多货
• 某工厂或类目看起来很便宜
• 已经有一批供应商候选

Default route:

1. inspect supply-side evidence
2. collect matching demand-side proof
3. test channel fit
4. synthesize

3. Demand-Led Sourcing Check

Use when the user already has a demand-side signal:

• Amazon 上卖得不错
• TikTok Shop 上很多人在卖
• 某类内容在 TikTok 很火

Default route:

1. inspect demand-side proof
2. collect supply-side feasibility
3. synthesize

4. Shortlist Comparison

Use when the user has:

• several products
• several niches
• several supplier options

Default route:

1. normalize each candidate into the same decision frame
2. compare strongest evidence and biggest gaps
3. rank cautiously

Capability Routing

Choose sources by role, not by habit.

Supply-Side Source

Use for:

• factory options
• supplier variety
• MOQ
• tiered pricing
• customization
• location

Current preferred route:

• skills/20-research/1688-research

Demand-Side Source

Use for:

• listings
• pricing
• reviews
• order or ranking proof
• bestseller shape
• channel-native competition

Current preferred routes:

• Amazon search-led demand -> skills/20-research/amazon-research

Search-Intent Source

Use for:

• early demand signals
• topic or keyword momentum
• geo search interest
• rising-query discovery

Current preferred route:

• Google search-intent -> skills/20-research/google-trends-research

Treat this as an early signal layer. Do not confuse it with transaction demand or channel-native competition proof.

Content-Language Source

Use when content-led selling matters:

• what hooks are working
• what user language repeats
• what visual demo style fits the product

Current preferred route:

• skills/20-research/tiktok-research

If the request is broader than one named platform and the goal is to compare social proof or audience language across networks, route first through:

• skills/10-routing/social-media-extractor

Use this layer only when it changes the decision. Do not force it into every sourcing task.

When social proof is cross-platform, do not let one familiar network stand in for the whole market. Use the extractor to decide which platform-specific research skill should collect first.

Extensibility Rule

When a new platform appears, do not rewrite the decision model.

Instead, map it into one of these roles:

• supply-side
• search-intent
• demand-side
• content-language
• finance
• compliance

Then state:

• what role the source covers
• what role is still missing

This keeps the skill stable while letting the source set expand.

Good Output

Return a compact decision memo with:

• product or niche
• target merchant model
• target channel
• observed evidence
• provisional judgment
• biggest risks
• missing layer
• recommended next step

Good recommendation shapes:

• promising, but demand proof still thin
• good Amazon search fit, weak TikTok demo fit
• cheap supply exists, but competition is commodity-price-led
• strong demand and workable sourcing, but returns or compliance may kill margin

If the result is going to move into execution, keep the handoff explicit:

• sourcing judgment -> merchant or channel decision
• merchant or channel decision -> research expansion, supplier outreach, or brief creation

Do not blur evidence collection, business judgment, and execution prep into one opaque step.

Failure Modes To Avoid

Do not:

• treat one platform's popularity as universal demand proof
• treat cheap 1688 supply as a recommendation by itself
• jump from TikTok content heat to Amazon launch logic without search proof
• jump from Amazon demand to TikTok Shop without content-demo fit
• hide missing finance or compliance layers

Current Workspace Default

At the moment, this skill should usually compose existing skills rather than create a brand-new collection workflow.

Current building blocks:

• supply-side: skills/20-research/1688-research
• search-intent: skills/20-research/google-trends-research
• search-led demand: skills/20-research/amazon-research
• content-language fit: skills/20-research/tiktok-research

Future sources should be slotted into the same roles.