Search Shipshape Data's library of 169 practical guides on data and AI. Each result includes the questions the guide answers and its URL (every page also serves a markdown twin at URL + index.md).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results, default 5 | |
| query | Yes | Search terms, e.g. "data lineage" or "RAG architecture" | |
| category | No | Optional category filter; one of the names from resource categories |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds useful behavioral context beyond annotations: each result includes the questions the guide answers and its URL, plus the note that a markdown twin exists at URL + index.md. This helps the agent understand the return format and available content.
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 first sentence front-loads the verb and resource; the second sentence provides valuable output details in compact form. 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?
This is a simple read-only search tool. The schema documents all parameters, annotations cover safety and idempotency, and the description explains what results contain. Nothing essential for correct invocation is missing. The markdown-twin note is a nice extra that improves usability.
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%, with query, limit, and category all documented in the input schema. The description adds no additional parameter-level meaning. It sits at the baseline expected when the schema carries the full weight of parameter documentation.
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 uses a specific verb ('Search') and clearly identifies the resource: 'Shipshape Data's library of 169 practical guides on data and AI.' This distinguishes it from sibling tools like get_case_studies or list_services, making the tool's scope unambiguous.
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 use the tool: when searching for practical guides on data and AI. However, it does not explicitly state when not to use it or mention alternatives, even though sibling tools like get_case_studies and list_services represent different resource types. Usage is implied rather than spelled out.
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.
Each tool has a clearly distinct purpose: retrieving assessment questions, scoring assessment answers, listing services, retrieving case studies, searching resources, and providing contact info. The only related pair—get_ai_readiness_questions and score_ai_readiness—are complementary rather than overlapping, with one delivering the questions and the other processing the answers.
All tool names follow a consistent snake_case verb_noun pattern: get, list, score, and search. The naming style is uniform and predictable, making it easy for an agent to infer behavior from the tool name alone.
Six tools is a well-scoped size for a company information and readiness-assessment server. Each tool contributes a distinct function with no redundancy, and the count is comfortably within the ideal range.
The tool surface covers the server's apparent purpose comprehensively: services, case studies, resources, contact information, and a complete AI readiness assessment flow. The explicit note that the server has no write tools appropriately sets expectations, and users can obtain URLs/markdown for deeper content.