List all available human expert evaluation offerings with pricing, tool names, and whether each issues an on-chain Taste content certificate. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| usage | Yes | ||
| status | Yes | ||
| service | Yes | ||
| offerings | Yes | ||
| nextOpenAt | Yes | ||
| onlineExperts | Yes | ||
| operatingHours | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It conveys a read-only listing operation and adds the detail that it is 'Free,' which is a useful cost-related behavior. It also specifies the return content (pricing, tool names, certificate status), but does not mention potential side effects like pagination, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the verb and object, then efficiently lists the key included attributes and the cost note. Every phrase earns its place without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with no parameters and an existing output schema, the description fully explains the tool's purpose, the data returned, and the free cost. It leaves no essential gaps for agents to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty with 100% coverage. The description correctly adds no parameter details, and the baseline for zero-parameter tools is 4, which is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List all available human expert evaluation offerings' with specific attributes (pricing, tool names, certificate issuance). This distinguishes it from sibling tools like list_expert_profiles, which focuses on profiles rather than offerings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for obtaining an overview of offerings but does not explicitly state when to prefer it over alternatives or when not to use it. It lacks differentiation from similar list-type siblings, so usage guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
All tool names follow a consistent verb_noun pattern with underscores, e.g., list_offerings, verify_certificate, request_human_approval. No mixing of conventions.
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.
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.