list_case_studiesLists seven case studies with slug, title, summary, headline figure, and URL; use a returned slug to fetch the full write-up.
The 7 case studies on his site: slug, title, one-paragraph summary, headline figure and URL. Pass a slug to get_case_study for the full write-up.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world scope, so the safety profile is covered. The description adds behavior beyond that: the fixed cardinality (7) and the exact shape of each returned record, which tells the agent it can rely on a small, stable, field-structured payload. Minor gap: no statement about ordering or whether the set can change.
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, zero waste. The return shape is front-loaded and the routing hint follows, so an agent gets the essential fact first.
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?
There is no output schema, so the description carries the burden of describing return values, and it does so field by field. For a no-parameter, read-only listing tool that is nearly complete; only ordering/stability of the list is unstated, which is low risk.
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, which is the baseline-4 case. The description is consistent with that — it never implies a filter or argument, and the mention of a slug is correctly attributed to the sibling get_case_study rather than to this tool.
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?
States a specific verb+resource (lists the 7 case studies) and enumerates exactly what each entry contains (slug, title, summary, headline figure, URL). It also names the sibling it is not: get_case_study returns the full write-up, so an agent can distinguish the index from the detail tool immediately.
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 second sentence routes the agent explicitly: use this to enumerate, then pass a slug to get_case_study for the full write-up. That is a clear use/alternative pairing. It stops short of an explicit exclusion (e.g. 'do not use this if you already know the slug'), so it is not a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.