Skip to main content
Glama

AI 代理人任務中樞

creator__check_ad_claims

[網紅開團合規工具箱]檢查台灣食品或化粧品廣告文案是否含涉及醫療效能、誇大不實的違規詞,回傳命中詞、風險等級、罰則與可用說法。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
categoryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It usefully discloses what the result contains (hit terms, risk level, penalties, acceptable alternatives), which helps. It does not state that this is a read-only/non-mutating check, nor any permission or rate-limit behavior, leaving real transparency gaps.

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?

A single front-loaded sentence that names the toolbox, the action, the detection target, and the return content with no wasted words. The bracketed prefix adds minor orientation rather than bloat.

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 no output schema and no annotations, the description steps in to describe the return value (hit terms, risk level, penalties, usable alternatives) and the detection scope, which covers most of what an agent needs. It stops short of clarifying permissions and the exact meaning of the category switch.

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 description coverage is 0%, so the description must compensate. It implicitly maps the two parameters (the 'ad copy' is the text input, and 'food or cosmetic' corresponds to the category enum), which is a partial compensation, but it doesn't clarify acceptable text format, length limits, or how category changes results.

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 (check) and resource (Taiwan food/cosmetic ad copy), and names exactly what it detects (medical-efficacy / exaggerated claims). An agent understands the tool's purpose immediately, though it does not explicitly contrast itself with nearby siblings like creator__endorsement_rules or creator__listing_checklist.

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?

The bracket label and phrasing imply usage ('influencer group-buy compliance toolbox' for ad copy), giving implied context. However there is no explicit when-to-use, when-not-to-use, or named alternative, so routing vs. the endorsement/listing siblings 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.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources