Check whether a user has access to a specific AI feature, such as CV evaluation, cover letter generation, or mock interviews, based on their subscription.
Check if the user has access to a specific AI feature based on their subscription.
| Name | Required | Description | Default |
|---|---|---|---|
| feature_name | Yes | The AI feature to check access for |
Changes observed during successful MCP inspections.
v3.2.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It implies a read-only check and notes the decision is subscription-based, but says nothing about required authentication, whether it can fail on unknown features, or the shape of the result.
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?
A single front-loaded sentence with no filler. The core purpose is stated immediately and nothing is wasted.
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 one-parameter read tool this covers the essentials, but with no output schema the description should state what is returned (a boolean, an entitlement object?) so the agent knows how to consume the result. It leaves the return contract implicit.
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 fully enumerated, so the schema already documents the feature_name value set. The description adds no format or constraint detail beyond the schema, making the baseline 3 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?
States a specific verb (check) and resource (access to a specific AI feature), with the gating factor (subscription) named. It is distinguishable from most siblings, though it does not explicitly differentiate from get_subscription_status, which addresses the same subscription domain.
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?
There is no when-to-use guidance, no prerequisites, and no mention of the related get_subscription_status or get_subscription_plans tools. The agent must infer that this is a pre-flight gate before generating features.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.