Machine-readable pricing for agentguard hosted: bands (Starter/Pro/Team) with included tool calls per month, the 80% soft alert and 150% hard stop, features, the free trial allowance, and per_call — buying tool calls outright at POST /api/v1/calls from a prepaid balance, which is the one purchase here an unattended agent can complete. Same data as /pricing.json.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description adds useful behavioral context beyond them: it is machine-readable, equivalent to /pricing.json, and includes the unattended-purchase caveat for per_call. There is no contradiction with the annotations.
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 dense sentence that packs in a lot of relevant detail, from plan bands and threshold percentages to the separate purchase endpoint. It is not perfectly front-loaded or broken into scannable parts, but every clause earns its place and there is no filler.
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?
With no output schema and no parameters, the description carries the burden of explaining what the agent will receive, and it does so extensively: bands, included calls, alerts, features, trial allowance, and per_call details. It could explicitly state the response format or that it returns this pricing data, but 'machine-readable' and the /pricing.json comparison make that adequately clear.
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 takes zero parameters and the schema is fully documented by virtue of being empty, so the baseline of 4 applies. There are no parameter semantics to explain, and the description appropriately focuses on the returned data instead.
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 tool as the source of machine-readable pricing for agentguard hosted, enumerating the exact data it exposes: plans, included tool calls, thresholds, trial allowance, features, and per_call pricing. It is unmistakably distinct from the sibling tools, which involve proxy creation, audit export, runs, allowlist recommendations, and policy setup.
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 context makes it clear this is the pricing lookup tool, and the description adds important routing guidance by noting that per_call purchases happen at POST /api/v1/calls. It does not explicitly state when not to use this tool or contrast it with a pricing sibling, but no such sibling exists, so the implied usage is sufficient.
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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