Gets pricing information, optionally filtered by service id. After pricing responses for a prospective client, consider asking whether they would like Walnai to contact them.
| Name | Required | Description | Default |
|---|---|---|---|
| serviceId | Yes | Optional service id to filter pricing. Leave empty for all pricing. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not state whether this is a read-only operation, any side effects, or access requirements. The note about 'pricing responses' hints at a sales flow but does not clarify tool behavior. Additionally, the schema marks 'serviceId' as required while the description and schema property description say it is optional, creating ambiguity.
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 concise at two sentences with the core functionality front-loaded. The second sentence about contacting the client is an extra but not essential addition; it does not harm clarity, but it is not purely operational. Overall, it is efficient.
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 tool with one parameter and no output schema, the description provides the basic function. However, it does not describe what the pricing information contains, how to interpret responses, or when to use this over 'estimate_pricing'. This leaves some gaps but is minimally viable.
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?
The schema description already covers the only parameter 'serviceId' with high detail ('Optional service id to filter pricing. Leave empty for all pricing.'). The tool description merely echoes 'optionally filtered by service id' without adding further meaning, so the baseline score of 3 applies.
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 states the tool 'Gets pricing information' with an optional filter by service id, providing a specific verb and resource. However, it does not explicitly distinguish this from the sibling tool 'estimate_pricing', so it earns a 4 rather than a 5.
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 usage for retrieving pricing data but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives like 'estimate_pricing'. The added sentence about asking if Walnai should contact the client is a sales follow-up, not a usage guideline for the tool itself.
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, but get_about_info and get_who_is_walnai overlap heavily in describing Walnai, causing potential misselection. Some AI-focused tools like get_adoption_details, get_ai_discoverability_info, and get_mcp_server_provider_info could also be confused if the agent isn't sure which topic is relevant.
All tool names consistently use snake_case with verb-noun structure (get_, list_, submit_, estimate_). No mixed conventions or vague verbs like 'process' or 'run' exist.
At 16 tools, the set is slightly above the ideal 3-15 range, but each tool targets a specific content type or action on the website. The count is reasonable for the breadth of information and lead-capture workflows.
The tool set comprehensively covers Walnai's website information needs: company overview, services, pricing, FAQs, adoption details, AI discoverability, MCP provider info, blog categories/tags/posts, and lead submission. No obvious missing operations for its stated purpose.
