list_examples

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds useful provenance context — the catalog is version-bound, shipped with this Studio release from GitHub — but says nothing about how many examples are returned, whether names/IDs are returned that can be fed to open_example, or ordering.

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 first sentence is well front-loaded and earns its place. The second sentence packs four sibling tool names into a parenthetical without explaining their differences, which adds noise rather than routing clarity, and the sentence structure is convoluted for what is a simple list operation.

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-param read tool with no output schema, the description covers purpose and workflow adequately. It leaves gaps an agent needs in practice: what the list entries look like, how to identify an example to pass to open_example, and what the language parameter changes.

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?

There is one optional parameter (language, enum ja/en/zh, default ja) with 0% schema description coverage, and the description never mentions it. The enum values are self-explanatory, but nothing explains whether the language affects the returned example names, descriptions, or reference data.

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 verb and resource ('List solved examples') and immediately qualifies what those are: 'verification cases already computed and checked against their closed-form reference, published with this Studio version on GitHub.' That definition implicitly separates it from list_cases and list_templates, though neither sibling is named, so an agent must infer the distinction.

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 gives a clear follow-on workflow: use open_example to get a case with its result, then inspect via get_results, verify_case, render_view, or probe_results 'before running anything.' That is genuine when-to-use context, but there is no explicit statement of when NOT to use this tool (e.g., when you already have a case name, or when list_cases is the better entry point).

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