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Glama

kdp_lookup

KDP/Amazon competitive data: BSR, pricing, review counts, niche score. $0.05/call via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinNo
keywordNo
categoryNo

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the cost per call and the type of data returned, which is useful. However, it does not disclose parameter requirements, error behavior, or access needs, leaving significant behavioral aspects unexplained.

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?

The description is a single, concise sentence that front-loads the purpose and includes a cost note without unnecessary detail. It avoids fluff and is easy to parse.

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

Completeness2/5

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

Given the tool has 3 optional parameters, no annotations, and no output schema, the description is significantly incomplete. It fails to explain how to use the parameters, what format the output will take, or any constraints (e.g., need for at least one parameter). The cost and data type list offer some context, but not enough for a new agent to use the tool correctly.

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

Parameters1/5

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

The input schema has 0% description coverage, and the description provides no information about the three parameters (asin, keyword, category). It does not clarify which parameter is required, how they interact, or what each controls, so the description adds no value for parameter understanding.

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?

The description clearly states the tool's function: 'KDP/Amazon competitive data: BSR, pricing, review counts, niche score.' It identifies the specific resource (KDP/Amazon) and the data types returned, which distinguishes it from sibling tools like company_lookup or crypto_price.

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 description implies usage for KDP/Amazon market research but provides no explicit when-to-use guidance or alternatives. The cost note ('$0.05/call via x402') is a usage consideration, but there is no mention of when to choose this tool over siblings or when not to use it.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: company lookup, crypto price, email verification, PDF extraction, KDP data, social profile lookup, YouTube transcription, and web reading. No two tools overlap in their primary function, so an agent can easily select the right one.

Naming Consistency3/5

Names follow a snake_case convention but mix verb-object (extract_pdf, transcribe_youtube) and object-verb (company_lookup, email_verify, web_read) orders. Also, crypto_price is noun-noun, breaking the verb pattern. The inconsistency is noticeable but names remain readable.

Tool Count5/5

With 8 tools, the server is well-scoped for a general-purpose utility API. Each tool adds a distinct capability without redundancy or bloat, fitting comfortably within the optimal 3-15 tool range.

Completeness4/5

The set covers common agent needs like web reading, PDF extraction, email verification, and social/company analysis. However, some obvious utilities like image processing or file conversion are absent, representing minor gaps but not severe dead ends.

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