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sticker_find

Finds up to three sticker text candidates by public emotion or action words, checking QQ favorites first, then a meme cache, and finally fixed sites.

Instructions

按 1~16 字公共情绪/动作词找表情:先查 QQ 收藏,再查已理解的联网梗图缓存,最后才去固定站点搜。返回最多 3 个文字候选。query 只写公共词(如“开心”“猫猫无语”),不传聊天原文、人名、QQ号;没有结果或冷却时本轮用文字,不要连续重试。

Input Schema

NameRequiredDescriptionDefault
queryYes1~16 字公共情绪/动作词,如 开心、无语、猫猫 无语
targetNo可选:会话标识 group:123456 / private:7890,用于额度与看图许可的归属

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the internal search order across three sources, the maximum candidate count, the existence of a cooldown state, and a privacy constraint on input. It stops short of describing what a '文字候选' actually contains or whether candidates must be passed to sticker_preview/sticker_send to be used.

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 search order, and every clause carries information (length limit, fallback chain, result cap, privacy, retry policy). The semicolon-chained Chinese phrasing is dense and slightly run-on, but nothing is redundant.

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?

For a 2-parameter tool with no output schema and no annotations, the description covers behavior, source priority, result volume, and error handling. The only missing piece an agent would want is the handoff to sticker_preview/sticker_send for the returned candidates.

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, and the description adds a real constraint beyond the schema: query must contain only public emotion/action words and must not carry chat text, names, or QQ numbers. It says nothing about the optional 'target' parameter, relying entirely on the schema for that.

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?

States a specific verb and resource ('找表情' by a 1–16 character public emotion/action word) and adds the resolution chain (QQ favorites → meme cache → fixed sites) plus a result cap of 3. It is clearly distinguishable from sticker_collect/list/send, but it never explicitly contrasts itself with those siblings.

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

Usage Guidelines5/5

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

Gives explicit when-to-use input rules (public emotion/action words only), explicit prohibitions (no chat transcripts, person names, or QQ numbers), and an explicit failure path ('没有结果或冷却时本轮用文字,不要连续重试'). The agent knows what to do both on success and on empty/cooldown outcomes.

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