Hero bio (pydantic-ai + sampling)

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose an important non-deterministic trait: the LLM is supplied by the client via MCP sampling, implying possible latency or failure if sampling is unsupported. It does not cover behavior when the codename is unknown or whether the operation has side effects.

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 one sentence, front-loaded with the main action, and contains no filler. The phrase 'pydantic-ai' repeats the title's parenthetical, which is a minor redundancy, but the description remains compact and readable.

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?

The tool is simple and an output schema exists, so return-value details are not required. However, the description lacks usage routing and failure/edge-case context, and with no annotations this leaves an agent with only a partial picture of when and how to call it safely.

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?

With 0% schema description coverage and no explicit explanation of `codename`, the description only implies that the codename identifies the hero whose facts are used. For a single required string parameter this is partially sufficient, but the expected format or source of valid values is not stated.

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 clear verb ('writes') and resource ('short in-universe bio') and identifies the source data ('hero's facts'), which separates it from sibling retrieve/list tools like get_hero or list_heroes. The pydantic-ai/sampling implementation detail slightly dilutes the purpose statement but does not obscure it.

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 guidance on when to prefer this tool over alternatives such as get_hero or find_heroes_by_power, and no exclusions or prerequisites are stated. The only implicit signal is that a bio is needed, which is not enough for confident tool selection.

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