List every OpenRTB version id this build can validate against, from 2.0 through the monthly 2.6 snapshots. Call this before pinning version on a validate_* tool.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| versions | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds meaningful context by specifying the version range (2.0 through monthly 2.6 snapshots) and the build-specific nature of the list. This goes beyond the structured annotations without contradicting them.
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 two sentences: the first states the core function, the second provides usage guidance. It is front-loaded, with no filler or repetition. Every sentence earns its place.
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 list/discovery tool with no parameters, a clear output schema, and strong annotations, the description adequately covers what the tool does, when to use it, and the expected scope. There are no missing pieces that would hinder correct invocation.
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 a parameter count of 0, the baseline is 4; the description need not explain parameter meanings. It focuses on the purpose, which is appropriate.
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 identifies the action ('List every OpenRTB version id'), the resource (versions this build can validate against), and the scope (from 2.0 through monthly 2.6 snapshots). It also distinguishes this discovery tool from the validate_* siblings by framing it as a prerequisite for them.
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 explicitly states when to use the tool: 'Call this before pinning version on a validate_* tool.' This provides clear context and establishes a relationship with the sibling tools. However, it does not explicitly state when not to use it or mention alternatives beyond the implicit validate_* family.
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 distinct aspect of the RTBlint domain: protocol discovery (get_adcp_capabilities), version enumeration (list_openrtb_versions), ARTF request and response validation (validate_artf_request, validate_artf_response), and OpenRTB payload validation (validate_bid_request, validate_bid_response). The descriptions clearly differentiate their purposes and invocation order.
All tools follow a consistent verb_noun pattern: get_adcp_capabilities, list_openrtb_versions, validate_artf_request, validate_artf_response, validate_bid_request, validate_bid_response. The naming is uniform, predictable, and clearly indicates the action and target.
With 6 tools, the set is well-scoped for the domain of RTB validation and protocol discovery. Each tool addresses a necessary function without redundancy or excess, making the server easy to navigate and integrate into an agentic pipeline.
The tool set covers key lifecycle steps: discovery, version selection, request validation, response validation, and cross-validation. A minor gap is the lack of a tool for validating mutations that don't involve ARTF, but the ARTF tools handle the core workflow well.
