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Human brand feedback

brand_feedback

Ask real humans a short brand or product question via WURK. Returns replies plus sentiment. Can take minutes. Costs 0.50 USDC, settled by POST https://api.bilbop.org/brand-feedback. payTo 2r2vsoyuYuy4dsyQVRhfmMBqsMRKHRS5FTPNumYFhxE4. Pay the resource URL in the 402 challenge, then retry with PAYMENT-SIGNATURE or X-PAYMENT forwarded by this MCP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoNumber of respondents (default 5)
brandYesBrand or product name
questionYesQuestion for human respondents

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations cover safety profile (readOnlyHint=false, openWorldHint=true, idempotentHint=false). Description adds critical context beyond annotations: latency, cost (0.50 USDC), and payment workflow (402 challenge, PAYMENT-SIGNATURE retry). This is substantial non-redundant behavioral info.

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-loads purpose, then latency, cost, and payment details. Some payment details are dense but necessary for correct invocation. No wasted sentences.

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?

Covers purpose, behavior, latency, cost, and payment flow. No output schema exists, so return values aren't detailed, but 'replies plus sentiment' gives sufficient characterization. Complete for safe invocation.

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%, so parameters (n, brand, question) are already documented. Description adds no parameter-specific semantics beyond the schema.

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+resource: 'Ask real humans a short brand or product question via WURK.' Clearly distinguishes from siblings (sol_mint_info, sol_token_brief, summarize, tts) which are unrelated utilities.

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?

Explains the mechanism, latency ('Can take minutes'), and output ('replies plus sentiment'). However it doesn't explicitly state when to use this over alternatives like summarize, though siblings are clearly different domains.

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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