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JavaScript
Remote

xiaohongshu_search_suggest

Fetch anonymous Xiaohongshu search suggestions for a partially typed keyword without login, returning suggested text, highlight flags, and search type.

Instructions

Anonymous Xiaohongshu search suggestions. Returns search suggestions for a partially typed keyword using a browser-minted signed request. Suggestions come from the site's own anonymous suggestion API and require no account or login. Each item carries the suggested text plus optional highlight flags and the suggestion's search type. Only the suggestion list is returned; search results need a logged-in session and are not exposed. The signer is a shared browser worker, so this endpoint is slower than the plain page endpoints (roughly a browser-backed request, not a single HTTP call); if no signer worker is available it returns 503.

Input Schema

NameRequiredDescriptionDefault
keywordYesPartially typed search keyword

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.18

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses the browser-minted signed request, that no account/login is required, that a shared signer worker makes it slower than plain HTTP endpoints, and that a missing worker yields 503. It also describes the returned item shape (suggested text, highlight flags, search type).

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 purpose and scope, then requirements and failure mode; all sentences are relevant. Slightly verbose in the parenthetical gloss on the signer ('roughly a browser-backed request, not a single HTTP call'), which repeats the preceding point.

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, but the description compensates by sketching the item contents and stating that only the suggestion list is returned. Auth requirements, latency expectations, and the 503 failure path are all covered, so an agent knows what it gets and what can go wrong.

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 the single parameter already documents itself ('Partially typed search keyword'). The description's phrasing adds only the prefix nature of the input, which the schema states, so baseline 3 applies.

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 and resource ('Returns search suggestions for a partially typed keyword') and explicitly disambiguates from real search: 'search *results* need a logged-in session and are not exposed.' An agent can immediately tell this is autocomplete-like, not a search endpoint.

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?

Implies the use case clearly (partially typed keyword, anonymous session) and effectively gives a when-not: full search results are unavailable here. It does not name a specific alternative sibling such as xiaohongshu_explore or xiaohongshu_note, so routing to a next step is left to inference.

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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