get_examples

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

With no annotations, the description carries the full burden, and it does disclose the important behavioral trait that the tool operates in two modes: a listing mode with no argument and a 'best match' retrieval mode with a topic. It does not describe permissions, ambiguity handling when no example matches well, or anything about result size, so the disclosure is partial.

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, no filler, with the enumeration and the conditional behavior front-loaded. 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 simple one-optional-parameter tool with an output schema already defining return shape, the description covers both invocation modes adequately. Only the topic-matching semantics remain underspecified.

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 0% and the single 'topic' parameter is undocumented in the schema, but the description compensates by explaining its effect: supplying a topic changes the output from a list to the best-matching example content. This is meaningful added semantics, though it omits matching behavior (fuzzy? exact?) and the null default's meaning.

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 and resource ('List bundled Serpent input examples') and enumerates the concrete example categories (pin cell, shielding, burnup, group constants, minimal sphere), so the agent knows exactly what comes back. It does not explicitly contrast itself with siblings like get_reference or search_docs, so it falls short of a 5.

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 description implies usage through its dual-mode sentence ('With topic, return the best matching example content'), but it never states when to prefer this tool over get_reference, search_docs, or get_card, nor any exclusion. Usage is inferable rather than guided.

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