Taste

consult_domain_expert

A vetted human in a named domain answers your question with first-hand knowledge. Pass domain to match an expert. Pass parentSessionId for follow-ups (cap 3). Returns answer, anonymised role, confidence, first-hand flag. Approved answers get an on-chain Taste cert. Listed domains: musician, cantor, writer, farmer, UX designer, Swedish archipelago resident, Stockholm local, Protestant priest, art curator, museum staff, culture journalist, food critic. Other domains: best-effort 24-48h.

Input Schema

TableJSON Schema

Name	Required	Description
`domain`	Yes	Area of expertise needed. Examples of currently listed domains: "Professional musician", "Cantor", "Writer", "Farmer", "UX designer", "Person living in the Swedish Archipelago", "Stockholm local", "Protestant priest", "Art curator", "Museum staff", "Culture journalist", "Food critic". Free-form — describe the kind of expert you need.
`context`	No	Optional. Why you are asking and what you are working on (essay, research, product decision, etc.). Helps the expert frame their answer.
`question`	Yes	The specific question to ask the expert. Be precise — the more specific the question, the better the answer.
`referenceUrls`	No	Optional. Publicly accessible URLs the expert should review before answering.
`parentSessionId`	No	Optional. If present, this is a follow-up question to the same expert on an existing consultation. Up to 3 follow-ups per parent. Server validates the parent is completed and within the follow-up cap.
`buyerWalletAddress`	No	Optional. An EVM wallet address. If provided, you can later retrieve the deliverable on humantaste.app by connecting this wallet.
`requireListedDomain`	No	Optional. If true, the job is declined immediately when the domain is not on the supported listed-domain list, instead of being queued for best-effort sourcing.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`tip`	Yes
`status`	Yes
`message`	Yes
`offering`	Yes
`priceUsdc`	Yes
`sessionId`	Yes
`parentSessionId`	No
`followupsRemaining`	No

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses return values (answer, anonymised role, confidence, first-hand flag), the on-chain Taste cert for approved answers, and the follow-up cap. It does not mention rate limits or failure modes, but the covered aspects are detailed and accurate.

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?

The description is a single paragraph that front-loads the core purpose and then covers parameters and behavior efficiently. It avoids redundancy and each sentence adds value, though it could be slightly more structured (e.g., bullet points). Overall, it is concise and readable.

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?

Given the tool's complexity (7 parameters, 2 required, output schema present), the description adequately covers the process, return values, and follow-up constraints. It lacks explicit error handling or non-listed domain behavior beyond 'best-effort 24-48h', but the essential information for an agent to use the tool correctly is present.

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%, but the description adds value by explaining that `domain` is free-form, `parentSessionId` is for follow-ups, `buyerWalletAddress` links to deliverable retrieval, and `requireListedDomain` controls immediate decline. This context goes beyond the schema's basic descriptions, aiding correct invocation.

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 explicitly states the tool matches a 'vetted human in a named domain' to answer questions with first-hand knowledge. It clearly identifies the verb ('answers'), resource ('human expert'), and scope ('named domain'), distinguishing it from general human query tools like ask_a_human. The listed domains and mention of best-effort for others further clarify its specific niche.

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?

The description provides clear guidance on when to use: pass a `domain` to match an expert, use `parentSessionId` for follow-ups (capped at 3), and lists recognized domains. It does not explicitly state when not to use it or compare to sibling tools, but the context of needing a vetted domain expert is implicit.

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

A4.4/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose, covering different aspects of human expert evaluation: dispute arbitration, domain consultation, content review, certificate verification, etc. Even similar tools like review_content and prepublish_review differ in their focus (facts vs. cultural sensitivity), and order_think_tank_session_30 and _60 only differ by duration, which is natural.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in lowercase with underscores (e.g., arbitrate_dispute, list_offerings, verify_certificate). There is no mixing of conventions or vague verbs, making the naming predictable and easy for an agent to infer functionality.

Tool Count5/5

With 17 tools, the server strikes a good balance—enough to cover a wide range of human expert evaluation tasks without being overwhelming. Each tool serves a specific, justifiable purpose within the domain.

Completeness4/5

The tool set covers core workflows like ordering evaluations, retrieving results, requesting revisions, and verifying certificates. However, there is no explicit tool for ordering an illustration (only revision), which is a minor gap. Overall, the surface is nearly complete for the stated purpose.

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