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meeting-brief

SMB: pre-meeting brief + talking points + questions. input=person/company. [x402: 2.0 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesservice input

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description must carry the full burden. It does disclose the pay-per-use cost (2.0 USDC on Base), which is a behavioral trait. However, it does not mention whether the operation is read-only, what happens with the input, or any side effects. Given the tool is likely a generation service with no destructive actions, the absence of such disclosure is not fatal but leaves gaps.

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, front-loaded line that leads with the core purpose, then the input type, then the pricing note. It is efficiently arranged with no wasted words, making it easy for an agent to quickly parse the essential information.

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 simple tool with one parameter and no output schema, the description covers the purpose, input semantics, and cost. It does not specify the output format, but since no output schema exists, the description's mention of 'pre-meeting brief + talking points + questions' gives a reasonable expectation. The omission of any usage context or error handling is minor for this complexity level.

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?

The schema describes the only parameter as 'service input', which is completely generic. The tool description adds meaning by specifying 'input=person/company', clarifying the expected content. This compensates for the schema's lack of detail, but does not specify the exact format (e.g., name, identifier) that the agent should provide.

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?

The description states the tool produces a pre-meeting brief with talking points and questions for a person/company, which gives a specific resource and output. It is clear enough to distinguish from siblings like meeting-minutes, though it lacks a crisp subject-verb-object structure and the 'SMB:' prefix is ambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. It does not mention any exclusions or circumstances that would make a different tool more appropriate, leaving the agent to infer usage from context. This falls short of the 'implied usage' level because there is no explicit contextual cue.

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

C2.6/5.0
Disambiguation1/5

The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.

Naming Consistency3/5

Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.

Tool Count1/5

160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.

Completeness3/5

The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.

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