Ask about this platform: capabilities, pricing, policies. Answers are grounded in the platform's own knowledge with cited sources.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | The question, in plain language (max 2000 chars). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does state that answers are grounded in the platform's own knowledge and include cited sources, which is a useful behavioral trait. However, it does not mention potential limitations (e.g., scope of knowledge, format of citations) or side effects (though obviously read-only). This is adequate but not rich.
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, efficient sentence that front-loads the tool's purpose and key behavioral trait (cited, grounded answers). There is zero wasted wording, making it highly concise and structured correctly.
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 Q&A tool with one parameter, no output schema, and no annotations, the description covers the essential intent and a behavioral guarantee (grounded, cited). It omits details like the answer format or whether the tool can refuse questions, but these are minor for such a straightforward tool. The description is reasonably complete.
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%, meaning the only parameter 'question' is fully described in the schema ('The question, in plain language (max 2000 chars)'). The description adds almost no additional semantic value beyond what the schema already provides, so the baseline of 3 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 clearly identifies a verb ('Ask') and a resource ('this platform'), with specific topics (capabilities, pricing, policies) and a grounding/citation promise. It is not a tautology and is more specific than a generic 'ask' tool, but it does not explicitly differentiate itself from sibling 'about' which might serve a similar purpose.
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 no explicit guidance on when to use this tool versus its siblings (about, confirm, list_actions, quote). It simply states what it does without exclusions or comparative context, leaving the agent to infer suitability.
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.
Most tools are clearly distinct: list_actions, quote, and confirm map to discovery, planning, and execution respectively. However, 'about' and 'ask' both serve an informational purpose, which could lead to a brief moment of ambiguity before reading their descriptions closely.
Five tools mostly follow a simple verb-based pattern (ask, confirm, quote) with one clear verb_noun (list_actions). 'about' stands out as a non-verb, creating a minor deviation from the otherwise consistent style.
With only 5 tools, the server is tightly scoped to its purpose: orientation, knowledge lookup, action discovery, quoting, and confirmation. Each tool earns its place without superfluous additions.
The core workflow is complete: discover actions (list_actions), plan a call (quote), and execute (confirm), with about/ask for platform understanding. A minor gap is the lack of a way to list or cancel pending quotes, but the essential lifecycle is covered.