Read one pricing function your workspace can use: its name, description, status, tags, cost per unit, cost multiplier, and input and output schemas. Its owner also sees whether a credential is saved for it. Needs a Last Price credential with function read scope.
| Name | Required | Description | Default |
|---|---|---|---|
| function_id | Yes | The pricing function UUID: id on a list_functions result. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as a read-only, idempotent, non-destructive operation. The description adds useful behavioral context beyond the annotations: the required Last Price credential scope and the owner-specific visibility of whether a credential is saved.
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 three tight sentences, front-loads the read operation, then lists the returned fields and prerequisite auth scope. Every sentence adds relevant information without repetition.
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 read-by-ID tool with a fully described single parameter and no output schema, the description is complete enough: it names the returned fields, the credential scope, and the owner-specific visibility nuance.
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%, and the single parameter is documented as a UUID that is the id from a list_functions result. The description does not add meaning beyond that schema text, so the baseline score 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 states a specific verb and resource: 'Read one pricing function.' It also scopes the tool to a single workspace-usable function and enumerates the fields returned, distinguishing it from list_functions and mutation siblings like create_function or update_function.
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 gives clear usage context by identifying the resource as one function and stating the required credential and scope. It does not explicitly name alternatives such as list_functions for discovery, but the context is sufficient for an agent to know this is a detail lookup by ID.
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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