lab.invoke_toolInvoke a free utility directly. For paid utilities, returns the HTTP endpoint and payment requirement so an x402-capable client can complete the call.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| input | Yes | ||
| idempotency_key | No | Stable identifier required for side-effecting tools and safe retries. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only say the operation is not read-only, not idempotent, and not destructive, so the description must carry behavioral context. It does disclose that paid utilities are not executed directly but returned as an x402-compatible endpoint/payment requirement; however, side effects, failure modes, and auth expectations for free utilities are absent.
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-loads the primary behavior ('Invoke a free utility directly'), and includes the paid-utility exception without padding. Every sentence earns its place.
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?
No output schema exists and no return shape is given for the free-utility case, nor does the description mention how to discover valid slugs or that input is utility-specific. An agent is left with enough to attempt a call but not enough to reliably prepare a correct invocation.
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?
With only 33% schema description coverage (only idempotency_key is documented), the description needed to explain slug and input. It only implies that a utility is being invoked; it does not say how the slug identifies a utility, what input should contain, or how the two are related.
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 concrete action ('Invoke') and target ('utility'), and it adds an important free-vs-paid behavioral distinction. It is not a tautology and is distinguishable from siblings like list_tools/describe_tool, though 'utility' itself is left undefined.
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 implies when to call it (to directly run a free utility, or to obtain payment details for a paid one), but it does not explicitly explain when not to use it or point to lab.list_tools/lab.describe_tool for discovering valid slugs. Use is inferred rather than routed.
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.