lab.get_capability_requestPoll a previously submitted capability request with its private status token.
| Name | Required | Description | Default |
|---|---|---|---|
| request_id | Yes | ||
| status_token | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds meaningful behavioral context by signaling that this is a polling operation and that the status_token is private/secret, which affects how the agent should handle and treat the parameter. No contradictions with 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, well-structured sentence that front-loads the action ('Poll') and includes both key qualifiers ('previously submitted', 'private status token'). There is no redundancy or 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?
For a simple two-parameter polling tool with readOnly/idempotent annotations, the description is largely sufficient: it names both required inputs and clarifies the operation. It does not describe the response shape or possible status values, but the tool has no output schema and the title/description already communicate 'status', so this is a minor gap rather than a critical omission.
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 0%, so the description carries the burden of explaining parameters. It does provide some semantic value: request_id maps to a 'previously submitted capability request' and status_token is characterized as 'private'. However, it does not explain how to obtain these values or give format/format expectations beyond the schema's length constraints.
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 uses a specific verb ('Poll') with a clear resource ('capability request') and outcome ('status'). It also qualifies the request as 'previously submitted' and requires a 'private status token', which distinguishes it from sibling tools like lab.request_capability without ambiguity.
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 phrase 'previously submitted capability request' clearly indicates this is for follow-up polling after submission, and the need for a 'private status token' sets expectations for authorization. It does not explicitly state when to prefer this over siblings, but the polling semantics are clear enough for an agent to select it correctly.
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.
Tools are mostly distinct: list, search, and describe serve different discovery needs (broad listing, intent-based search, detailed metadata), while invoke, request, and poll cover execution and capability requests. The slight overlap between list_tools and search_tools is mitigated by clear descriptions and usage guidance.
All tool names follow a consistent verb_noun snake_case pattern with the lab prefix, such as invoke_tool, list_tools, and request_capability. The naming is predictable and easy to navigate.
Six tools is a well-scoped size for a utility marketplace/agent enhancement server. Each tool covers a necessary function without redundancy or bloat.
The tool set covers the core lifecycle: discover, inspect, invoke, request new capabilities, and poll request status. Minor gaps like canceling a capability request or managing usage history are absent, but the main workflows are complete.