case_studiesOur anonymized case studies: title, summary and links. Use read_page for the full text.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "case_studies"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| cases | Yes | ||
| next_step | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It usefully discloses that content is anonymized and returns only title/summary/links, and that full text lives elsewhere, but says nothing about list size, pagination, ordering, or caching. With a rich output schema present, the remaining omission is moderate rather than critical.
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 short sentences with zero filler; the primary content description is front-loaded and the follow-up action (read_page) comes second. Every clause 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?
With an output schema present, the description need not explain return values, and with zero parameters there is no input surface to document, so the remaining burden is light. It covers transparency ('anonymized') and the handoff to read_page; only list-level behaviors like pagination are unaddressed.
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 tool takes zero parameters (empty object schema, additionalProperties false), so there is no parameter meaning to convey and the baseline of 4 applies. Nothing in the description misrepresents the parameterless interface.
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 resource (anonymized case studies) and enumerates the returned fields (title, summary, links), which lets an agent distinguish it from sibling 'company' or 'service_area'. It also explicitly routes deep-dive reading to read_page, giving sibling differentiation. It stops short of a 5 only because 'case studies' largely restates the tool name.
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?
It clearly names the alternative and the condition that selects it: fetch this list for summaries, then 'Use read_page for the full text.' What's missing is an explicit statement of when this tool is the right first step (e.g., browsing/listing) versus when it should be skipped, so it is clear context without full exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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