List SynergyBoat services as shown on synergyboat.com: id, name, and outcome summary for each. Use get_service for full details.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Optional localized content variant. Defaults to the global English content. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers safety, and the description adds source context ('as shown on synergyboat.com') and the output fields. However, it does not disclose any additional behavioral traits such as locale defaulting or pagination limits, though none are necessarily expected for a simple list operation.
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 concise, front-loaded sentences cover purpose, source, output content, and the sibling alternative. Every word earns its place, and there is no fluff or repetition.
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 read-only list tool with one optional parameter and no output schema, the description adequately states the output fields and points to the detailed sibling tool. The locale parameter is covered by the schema, so the overall context is complete enough for an agent to select and invoke the tool correctly.
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 fully describes the only parameter 'locale' with an explicit description and enum values. The description adds no parameter-specific meaning, but with 100% schema coverage, a baseline score 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 states a specific verb ('List'), a specific resource ('SynergyBoat services'), and the exact scope ('as shown on synergyboat.com'). It also lists the output fields (id, name, outcome summary) and explicitly contrasts with get_service, making the tool's purpose unmistakable.
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 clearly points to get_service for full details, providing a concrete alternative. It implies this tool is for summary-level browsing but does not mention when to prefer other sibling list tools like list_ai_use_cases or list_case_studies.
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: getters for individual items, listers for collections, and lead forms. The only potential confusion is between request_demo and submit_lead, but their descriptions clarify that one is for demo requests and the other for general enquiries.
All tools follow a consistent verb_noun pattern (get_*, list_*, request_*, submit_*), with snake_case throughout. No mixed conventions or vague verbs.
With 9 tools, the surface is appropriately scoped for a company information and lead generation server. Each tool serves a clear purpose without unnecessary bloat.
The server covers the main domain areas: company overview, services, case studies, team, AI use cases, and lead generation. However, list_ai_use_cases only provides an overview with no getter for full AI use case details, which is a minor gap.
