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LinkDigest — Xiaohongshu, Douyin, TikTok, YouTube to text

Compare a set of posts in one page

compare_links
Read-only

Read a set of Xiaohongshu, Douyin, Weibo, TikTok, YouTube or X links as one batch and write one comparison over them (批量综合): the themes, hooks, formats and claims they share, the objections readers raise and the gaps none of them cover, every example naming which link it came from and checked against it word for word. The first call starts the batch and returns a batch id; call again with batch_id to collect. Needs an API key. Each link is read at its usual price (cached links are free); the comparison is 1 credit per 10 links. Example: urls=["https://xhslink.com/o/a", "https://xhslink.com/o/b"]. After the browser extension's “Digest the notes on this page” button, call list_batches and pass the newest batch_id here.

Input Schema

NameRequiredDescriptionDefault
urlsNoThe post links, 1 to 20. Required unless batch_id is given.
insightNoAlso draw every post's consumer insight (消费者洞察) and compare on it. +1 credit a link.
batch_idNoCollect a batch still running, instead of urls (re-sending the urls would start it again).
breakdownNoAlso take every post apart (爆款拆解) so the comparison sees each hook and format. +1 credit a link.
translate_toNoWrite the comparison (and each digest) in this language, e.g. en. +1 credit a link.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (readOnly, openWorld, non-idempotent, non-destructive), the description discloses the things an agent most needs: an API key is required, the first call is not the final result (batch id + collect pattern), and each link is billed at its usual price with cached links free and the comparison at 1 credit per 10 links. The schema also warns that re-sending urls restarts the batch, consistent with idempotentHint=false.

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

Conciseness4/5

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

Front-loaded with the core action and output contents, then workflow, then cost, then example — a sensible order. It is dense with parenthetical bilingual labels and pricing details that make it longer than strictly needed, but nearly every clause carries information an agent needs.

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

Completeness5/5

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

No output schema exists, and the description compensates by describing what the comparison contains and that the first call returns a batch id. Auth, cost, and the async collect pattern are all covered, so an agent can invoke and follow up correctly without further information.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds value the schema lacks: a concrete urls example, the batch_id-driven collect pattern, and the credit cost of insight/breakdown/translate_to (+1 per link each). It stops short of explaining the exact comparison output shape for each flag.

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

Purpose5/5

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

States a specific verb (read as one batch, write one comparison) over a specific resource (a set of links from named platforms), and enumerates what the output contains: shared themes, hooks, formats, claims, objections, gaps, with every example attributed to a source link. This is clearly distinguishable from digest_url (one link) and search_links (find links).

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

Usage Guidelines4/5

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

Gives concrete when-to-use context (after the browser extension's 'Digest the notes on this page' button, call list_batches and pass the newest batch_id here) and explains the two-call lifecycle: first call starts the batch and returns a batch id, later calls collect with batch_id. It does not explicitly contrast with digest_url for the single-link case, so the exclusion is only 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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