lab.request_capabilitySubmit a free, private backlog request when no existing utility solves a concrete problem. Do not include secrets, personal data, or full conversation history.
| Name | Required | Description | Default |
|---|---|---|---|
| problem | Yes | ||
| constraints | No | ||
| evidence_urls | No | ||
| example_input | No | ||
| desired_outcome | Yes | ||
| expected_output | No | ||
| client_request_id | No | ||
| why_existing_tools_fail | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains that this creates a private backlog request, which complements the annotations. It also adds useful data-handling guidance by warning against including secrets or personal data. It does not deeply cover submission behavior or response semantics, but the core mutation nature and privacy posture are clear.
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?
Two sentences with no filler. The primary purpose and usage condition are front-loaded, and the second sentence adds a concrete safety instruction that 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?
For a tool with eight parameters, a nested constraints object, and no output schema, the description is too thin to guide correct invocation. It does not explain how to fill required fields, what constraints mean, how evidence URLs should be used, or what happens after the request is submitted.
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 must compensate, but it explains none of the eight parameters. The required fields problem, desired_outcome, and why_existing_tools_fail are not described, and the nested constraints object with retention options is entirely unaddressed. Parameter names are suggestive but the description adds almost no semantic value.
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 action ('Submit a free, private backlog request') and the condition under which it applies ('when no existing utility solves a concrete problem'). This clearly differentiates it from sibling tools that list, search, invoke, or describe existing tools.
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 a clear usage condition: use it only when no existing utility solves the problem. It also warns about what not to include (secrets, personal data, full conversation history). It does not explicitly name alternatives like lab.search_tools, but the intended routing is reasonably clear.
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.