TokConnect: TikTok Research

A creator's TikTok Shop business

creator_commerce

Read-onlyIdempotent

What a creator sells. Live: linked_products (products linked in recent posts, with views; no sales). [Shop Analytics, any market via region]: sales (revenue, units, video vs LIVE), trend (daily), products (with revenue), shops (brands they sell for), videos (selling videos), audience (follower age, gender, locations, languages; says so when it has not been built). Use to vet affiliates. Example: {"id":"@dollskill","method":"products","window":"90d"}.

Input Schema

Name	Required	Description	Default
`id`	Yes	Creator: @handle, profile or video link, secUid (MS4wLjAB...) or numeric user id. TokConnect looks up the ids it needs.
`end`	No	Shop Analytics methods: custom range end, YYYY-MM-DD (capped at the last complete day).
`limit`	No	Results per page. Shop Analytics methods max 100. Values above a method's maximum are lowered and reported in notes.
`start`	No	Shop Analytics methods: custom range start, YYYY-MM-DD.
`cursor`	No	Paging: pass the next value from the previous response unchanged. Omit on the first page.
`detail`	No	compact (default) returns the useful fields; full adds the full raw record (large).	compact
`method`	No	What to get. linked_products: each product linked in recent posts, with post count, views and likes (not sales) \| sales [Shop Analytics]: revenue, units, video vs LIVE, average price \| trend [Shop Analytics]: daily revenue (up to ~13 months) \| products [Shop Analytics]: products they sold, with revenue \| shops [Shop Analytics]: shops (brands) they sell for, with revenue \| videos [Shop Analytics]: their selling videos, with revenue \| audience [Shop Analytics]: follower age, gender, top locations and languages, active hours (when Shop Analytics has built it)	sales
`region`	No	Market as an ISO country code, default US. Shop Analytics methods: sales data for that market, amounts in its currency. Live methods that take it (search, video detail, creator posts, Shop pages): TikTok as seen in that market where TikTok serves it. Core: US, GB, DE, FR, ES, JP, TH, VN, ID, MY, PH, BR, MX. Extended: PL, IT, NL, IE. Other countries are refused. See shop_regions.
`window`	No	Shop Analytics methods: date range ending at the last complete day (about 2 days ago). Default 30d. Use start/end for a custom range.
`max_pages`	No	method=linked_products: post pages to scan, 15 posts each (default 3, max 5).

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 2, 2026

changedInput schema / properties / detail / description

Previous value: -"compact (default) returns the useful fields; full adds the raw upstream payload (large)."New value: +"compact (default) returns the useful fields; full adds the full raw record (large)."

changedInput schema / properties / method / description

Previous value: -"What to get. linked_products: each product linked in recent posts, with post count, views and likes (not sales) | sales [Shop Analytics]: revenue, units, video vs LIVE, average price | trend [Shop Analytics]: daily revenue (up to ~13 months) | products [Shop Analytics]: products they sold, with revenue | shops [Shop Analytics]: shops (brands) they sell for, with revenue | videos [Shop Analytics]: their selling videos, with revenue | audience [Shop Analytics]: follower age, gender, top locations and languages, active hours (when the source has built it)"New value: +"What to get. linked_products: each product linked in recent posts, with post count, views and likes (not sales) | sales [Shop Analytics]: revenue, units, video vs LIVE, average price | trend [Shop Analytics]: daily revenue (up to ~13 months) | products [Shop Analytics]: products they sold, with revenue | shops [Shop Analytics]: shops (brands) they sell for, with revenue | videos [Shop Analytics]: their selling videos, with revenue | audience [Shop Analytics]: follower age, gender, top locations and languages, active hours (when Shop Analytics has built it)"

Changed1 schema field changedOct 31, 2026

changedInput schema / properties / region / description

Previous value: -"Shop Analytics methods: market as an ISO country code, default US. Core: US, GB, DE, FR, ES, JP, TH, VN, ID, MY, PH, BR, MX. Extended: PL, IT, NL, IE. Other countries are refused. Amounts are in the market's currency. See shop_regions."New value: +"Market as an ISO country code, default US. Shop Analytics methods: sales data for that market, amounts in its currency. Live methods that take it (search, video detail, creator posts, Shop pages): TikTok as seen in that market where TikTok serves it. Core: US, GB, DE, FR, ES, JP, TH, VN, ID, MY, PH, BR, MX. Extended: PL, IT, NL, IE. Other countries are refused. See shop_regions."

Changed2 schema fields changedOct 21, 2026

changedInput schema / properties / method / description

Previous value: -"What to get. linked_products: each product linked in recent posts, with post count, views and likes (not sales) | sales [Shop Analytics]: revenue, units, video vs LIVE, average price | trend [Shop Analytics]: daily revenue (up to ~13 months) | products [Shop Analytics]: products they sold, with revenue | shops [Shop Analytics]: shops (brands) they sell for, with revenue | videos [Shop Analytics]: their selling videos, with revenue | audience [Shop Analytics]: follower age, gender and language"New value: +"What to get. linked_products: each product linked in recent posts, with post count, views and likes (not sales) | sales [Shop Analytics]: revenue, units, video vs LIVE, average price | trend [Shop Analytics]: daily revenue (up to ~13 months) | products [Shop Analytics]: products they sold, with revenue | shops [Shop Analytics]: shops (brands) they sell for, with revenue | videos [Shop Analytics]: their selling videos, with revenue | audience [Shop Analytics]: follower age, gender, top locations and languages, active hours (when the source has built it)"

addedInput schema / properties / region

Added value: +{
+  "description": "Shop Analytics methods: market as an ISO country code, default US. Core: US, GB, DE, FR, ES, JP, TH, VN, ID, MY, PH, BR, MX. Extended: PL, IT, NL, IE. Other countries are refused. Amounts are in the market's currency. See shop_regions.",
+  "maxLength": 2048,
+  "type": "string"
+}

AddedOct 20, 2026

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnly/openWorld annotations, the description discloses that linked_products has views but 'no sales', that audience 'says so when it has not been built', and that some markets are refused. Those are real behavioral caveats an agent could not derive from annotations alone.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the one-line purpose, then method inventory, then usage and a worked example. Telegraphic phrasing ([Shop Analytics, any market via region]) is dense but every clause carries information and nothing is padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 10 parameters, an output schema, and rich annotations, the description covers the important gaps: method semantics, region limits, unbuilt-data behavior, and a call example. Only the sibling-selection and pagination story is left thin.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and each parameter already documents its per-method applicability, so the description's bracketed '[Shop Analytics]' tags largely restate the schema. It adds only marginal value, such as the example payload showing method/window composition; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening line 'What a creator sells' plus the enumerated method outputs (revenue, units, products, shops, videos, audience) makes the resource and the returned data concrete. It doesn't explicitly name the sibling `creator` or `creator_top_selling`, so an agent must infer that this is per-creator commerce data rather than a creator ranking or profile.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use to vet affiliates' supplies one concrete scenario, and the Live vs Shop Analytics split routes between method families. But there is no guidance about when to prefer `creator`, `shop`, or `product` instead, and no exclusions, so tool-level routing remains implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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