Run a cached worked example

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden. It clearly discloses that the tool is fully offline, uses cached papers, requires no API key, and needs no network, which are the key behavioral traits an agent needs before invoking it. It does not detail output format or error behavior, but those are minor for a simple example runner.

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?

The description is front-loaded with the core purpose, followed by the offline advantage and then a structured list of options. Every sentence earns its place, and the longer option details are necessary because the enum values are otherwise opaque.

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 single-parameter tool with no output schema, the description covers all invocation-critical information: what the tool does, why to use it, and valid parameter values. The only minor gap is that it does not explicitly describe what the returned output looks like, but the phrase 'grounded output' plus the example details make the behavior reasonably clear.

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 only lists the enum values with a generic description, while the tool description richly unpacks each option: concrete papers, years, and the nature of each contradiction. This gives an agent far more than the schema alone and makes parameter selection informed and accurate.

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 ('Run') and a specific resource ('built-in worked examples'), then names the exact examples with the contradictions they demonstrate. It is clearly distinct from a general study-comparison tool because it emphasizes cached, built-in, offline examples.

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 explicitly states when to prefer this tool: when you want the quickest demonstration of grounded output without an API key or network access. It does not explicitly name alternatives like compare_studies or state when not to use it, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.