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by app.humantaste

prepare_consult_domain_expert

Get a humantaste.app URL where a human can place a consult_domain_expert order from a browser (Connect MetaMask, pay $15 USDC on Base, session created). Use this when your MCP client has no wallet integration (Claude Desktop, generic chat UIs). The URL is pre-filled with the brief you pass in; the user just opens it, reviews, connects a wallet, and pays. Returns the payment URL and the price. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesArea of expertise needed (e.g. Farmer, Protestant priest, UX designer, Stockholm local, art curator, museum staff, culture journalist, food critic).
contextNoOptional. Why you are asking and what you are working on.
questionYesThe specific question to ask the expert.
referenceUrlsNoOptional. Publicly accessible URLs the expert should review.
parentSessionIdNoOptional. If present, the URL submits a follow-up to an existing consultation (capped at 3 per parent, same expert).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tipYes
messageYes
priceUsdcYes
paymentUrlYes

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries full burden. It discloses the full user flow (user opens URL, connects wallet, pays $15 USDC), states the session is created, names return values (payment URL and price), and clarifies the tool call itself is free. This is rich behavioral context.

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?

Four sentences, around 85 words, front-loaded with purpose. The details about payment and user flow are relevant, though 'Free' at the end could be more integrated. No fluff, each sentence earns its place.

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

Completeness5/5

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

Given an output schema exists, the description need not explain return format. It fully covers purpose, use case, user interaction, pricing, and result. It complements the schema by explaining the browser-based workflow and the distinction from sibling tools, making it complete for a tool of this complexity.

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 baseline is 3. The description adds meaningful semantics by explaining the URL is pre-filled with the passed brief, and clarifies the pricing context ($15) which is not in the schema. This elevates it to 4.

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 gets a humantaste.app URL for placing a consult_domain_expert order, with specific details about wallet connection and payment. It distinguishes itself from direct invocation tools by emphasizing the browser-based flow for clients without wallet integration.

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?

Explicitly says 'Use this when your MCP client has no wallet integration (Claude Desktop, generic chat UIs)', providing clear when-to-use guidance and an implicit alternative (consult_domain_expert sibling).

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

A4.2/5.0
Disambiguation5/5

Each tool targets a specific action or domain, with clear distinctions between similar ones (e.g., review_content vs prepublish_review for different review purposes, order_think_tank_session_30 vs _60 by duration). No ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with underscores, e.g., list_offerings, verify_certificate, request_human_approval. No mixing of conventions.

Tool Count4/5

17 tools is on the higher side but fully justified given the broad scope: expert consultations, think tanks, content reviews, verification, and human approval. Each tool serves a distinct purpose.

Completeness4/5

Covers the full workflow from discovery to ordering, revision, and on-chain verification. Minor gaps exist (e.g., no order cancellation or history listing), but core operations are well-represented.

Resources