search_jobs

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

Beyond the annotations (readOnlyHint: true, openWorldHint: false), the description discloses several behaviors: results are ordered by estimated salary descending, skill values are restricted to a fixed set with rejection on others, location accepts partial names when unambiguous, min_salary represents average annual USD, limit defaults to 5 with a range of 1-25, and the return includes total_matches alongside the returned slice. It also notes that 'each posting costs context,' which is a valuable operational detail. No contradiction with annotations.

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 front-loaded with the core purpose, followed by a clearly structured list of arguments. Each parameter entry is concise yet complete, with examples and caveats. The note about context cost is brief but relevant. No wasted words; the structure aids quick parsing.

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 4 parameters with no schema descriptions and an output schema (which likely covers the return shape), the description covers all necessary aspects: what it does, how to specify each filter, expected return info (total_matches and slice), and operational nuances. The agent has enough to correctly invoke the tool without ambiguity. The description even prompts reading a snapshot for location values, indicating a richer context.

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 description carries the full burden for parameter meaning. It explains each parameter in detail: skill lists allowed values and rejection behavior, location specifies format and partial matching, min_salary gives an example value and unit, and limit states range, default, and usage advice. This is exceptional compensation for the missing schema documentation.

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 clear verb+resource+scope: 'Find Data Analyst job postings, highest estimated salary first.' It specifies the resource (job postings), the target role (Data Analyst), and the ordering. This distinguishes it from sibling tools like salary_benchmark and skill_demand by topic, even without naming them.

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 provides usage tips for parameters, such as 'Read market://snapshot for the most common values before guessing' for location and 'Ask for more only when the user explicitly wants a long list' for limit. However, it does not explicitly say when to use this tool versus its siblings (salary_benchmark or skill_demand), nor does it mention any exclusions or alternatives. The context is implied by the purpose but not explicitly stated.

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