get_example

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

No annotations are provided, so the description is the only source. It discloses that the tool returns canonical, CI-validated example code. It does not mention side effects, authentication, rate limits, or response format, but these are likely minimal for a code retrieval tool.

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 three sentences: first states purpose, second gives usage guidance, third lists values. It is concise, front-loaded, and every sentence adds value.

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?

Given the simplicity of the tool (two parameters, no output schema), the description provides sufficient context: what it returns, when to use, and valid inputs. It could briefly mention the output format (e.g., code block), but overall it is complete.

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 description coverage is 100%, so the baseline is 3. The description lists the topic and language options, but the schema already does that via parameter descriptions. No additional semantic information (e.g., format, examples) is added beyond the schema.

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 clearly states the tool returns canonical FLOX example code for a topic, optionally filtered by language. It specifies valid topics and languages, and gives a concrete use case ('show me how to ...'), which distinguishes it from sibling tools like run_backtest or scaffold_strategy.

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 explicitly tells when to use this tool: when the user asks for a code example before writing fresh code, because examples are CI-validated. It doesn't mention when not to use or name alternative tools, but the context is clear.

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