Fetch AI ethics case studies, such as The Refusal Problem, to explore worked examples for ethical reasoning. Specify an index for one study or omit for all.
Read an item from M3 — Case Studies (worked examples such as The Refusal Problem).
| Name | Required | Description | Default |
|---|---|---|---|
| index | No | Item index (0–2). Omit for the whole module. |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Read' does imply a non-destructive read operation, which is the key behavioral fact for this tool, but the description says nothing about an omitted-index call returning the whole module, nor about return shape or error behavior.
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?
A single front-loaded sentence that identifies the module and gives a concrete example, with no filler. 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?
For a one-optional-parameter read tool there is little to specify, and the schema covers the parameter. But with no output schema and no annotations, the description does not indicate what a single-item read versus a whole-module read returns, leaving a modest gap.
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 coverage is 100% with a single optional parameter, so the schema already explains index (0–2) and 'omit for the whole module.' The description adds nothing about the parameter and even frames the tool as reading 'an item,' slightly at odds with the whole-module mode. Baseline 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?
States a specific verb ('Read') and resource ('an item from M3 — Case Studies') and even gives concrete content examples (The Refusal Problem). An agent can distinguish it from get_principle or get_code_of_conduct by the resource named, though it never names those siblings explicitly.
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?
There is no when-to-use or when-not-to-use guidance and no mention of alternatives among the many sibling retrieval tools. The agent must infer that this is the right tool for case-study content purely from the resource name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.