find_examples

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

Annotations already carry the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the description is not obligated to restate that. It adds no behavioral context beyond purpose: nothing about result ranking, whether the corpus is the live docs index, or what happens with empty inputs. Adequate but thin given how little the annotations leave unstated.

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 core purpose front-loaded before the usage triggers. Every clause carries information the agent needs.

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?

An output schema exists, so return values need not be explained, and the annotations cover safety. What is missing is any guidance on parameter behavior: the query and language defaults are empty strings and max_results defaults to 8, none of which is documented in either the schema or the description.

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 0%, so the schema alone tells an agent nothing about the three parameters. The description partially compensates by mapping query to "topic" and by enumerating language values (Python, TypeScript, Rust), which is genuinely useful since the schema has no enum. It says nothing about max_results or the empty-string default for query, so the compensation is incomplete.

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 opens with a specific verb and resource ("Find code examples in the LaserData documentation") and adds two scoping facets: topic and language. It is easy to distinguish from list_docs or get_doc, though it never explicitly contrasts itself with the closest sibling, extract_code_snippets, so the boundary between them must be inferred.

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 an explicit trigger clause ("Use this when a user asks for runnable examples, Laser SDK examples in Python, TypeScript or Rust, agent or session samples, or CLI commands"), which covers several realistic request shapes. It stops short of stating when not to use it or naming an alternative tool for overlapping needs.

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