Search by skill

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

With no annotations, the description must disclose behavior independently. It states what the tool searches (work experiences and projects) but omits critical behavioral details such as the return format (list of matches? snippets?), whether matching is fuzzy or exact, and whether the search scope is limited to a specific resume/document. The description does not adequately convey the tool's behavior beyond its basic purpose.

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 a single concise sentence that immediately states the tool's purpose. It is front-loaded with the action and resource, contains no fluff, and every word contributes to meaning. This is an example of compact, effective wording.

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 tool has one parameter, no output schema, and no annotations, the description should compensate by explaining what the results look like and the search behavior. It fails to mention whether the output is a list of experiences/projects, whether it includes context snippets, or if the search applies to the entire resume or a specific section. The description is too sparse to be considered complete for a search tool.

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% (the 'skill' parameter includes examples and a clear description). The tool description largely paraphrases the schema ('a given skill or technology') without adding new meaning. It does not clarify nuances like case sensitivity, partial matches, or how to pass multiple skills. Baseline 3 is appropriate because the schema already carries the semantic weight.

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 specific verb ('Find') and clearly identifies the resource ('work experiences and projects') and the criterion ('where a given skill or technology was used'). It effectively distinguishes from sibling tools like get_summary and get_section, which are about retrieving entire sections rather than searching by skill.

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 its usage context: when you need to locate experiences/projects using a specific skill. However, it provides no explicit guidance on when not to use it or how it compares to alternative tools (e.g., get_section for broader overviews). The lack of explicit alternatives or exclusions places it at 'implied usage' rather than clear context with exclusions.

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