Get machine-readable pricing for all Trillboards products. Returns graduated usage-based pricing, free tier thresholds, and committed-use discount tiers. No authentication required — use this to evaluate costs before integrating.
| Name | Required | Description | Default |
|---|---|---|---|
| product | No | Optional: filter to a specific product (data_api, proof_of_play, attribution, data_marketplace, partner_platform, programmatic, fein_edge_ai) |
Changes observed during successful MCP inspections.
Input schema / properties / product / descriptionAdded value: +"Optional: filter to a specific product (data_api, proof_of_play, attribution, data_marketplace, partner_platform, programmatic, fein_edge_ai)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the no-auth requirement and describes the return format and content (graduated pricing, free tier, discount tiers). This is meaningful behavioral context. It doesn't explicitly state that the operation is read-only, but the 'get' verb implies it, and no side effects are suggested.
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, front-loaded with the core purpose, and every sentence adds value. The second sentence packs return details, auth requirement, and use case without fluff.
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 tool with one optional parameter and no output schema, the description covers purpose, return contents, auth, and intended use. It could explicitly state the behavior when 'product' is omitted (e.g., returns all products), but the phrase 'all Trillboards products' implies this. Overall, the description is sufficient for an agent to select and invoke the tool.
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?
Schema description coverage is 100%: the single optional 'product' parameter is fully described with an enum of values. The tool description doesn't add any extra parameter semantics beyond the schema, so the baseline of 3 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 states the tool's purpose with a specific verb and resource: 'Get machine-readable pricing for all Trillboards products.' It also enumerates return contents (graduated usage-based pricing, free tier thresholds, committed-use discount tiers), which differentiates it from sibling tools like get_products or get_billing_status.
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 provides a clear use case: 'use this to evaluate costs before integrating.' It also mentions the authentication requirement (none). However, it doesn't explicitly name alternative tools or state when not to use it, so it falls short of a 5.
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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