Search Kansas City developer jobs

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

With no annotations provided, the description carries the full disclosure burden. It goes beyond the schema by disclosing the data source ('Data is live from kcdevs.com' — implying freshness and external origin) and describing the return shape (company, location, salary, apply link). For a search tool this is solid behavioral context, though it doesn't address pagination mechanics or result limits beyond the per_page schema field.

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?

Three sentences with zero waste: scope first, then filters, then return shape and data source. Front-loaded with the core purpose before enumerating filter options. Every sentence earns its place and nothing is redundant with the schema.

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?

For a search tool with a rich 9-parameter schema at 100% coverage, the description covers the essential non-schema facts: geographic scope, live data source, and return fields. Minor gaps include unspecified pagination behavior and no mention of how results are ordered when no sort is given (beyond the schema default 'newest'). These are small against the overall coverage.

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 coverage is 100% — all 9 parameters have descriptions. The description recapitulates the filter dimensions (keyword, category, skill, experience, remote type, salary, recency) but adds no meaning beyond the schema's own parameter descriptions. Baseline 3 applies because the schema already does the heavy lifting; the description merely confirms the dimensions without adding syntax, defaults, or interaction notes.

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 states a specific verb (search) and a clearly bounded resource (live software-developer/tech jobs in the Kansas City area and KC-based remote roles). It lists the filter dimensions, making the tool's scope unmistakable and differentiating it from siblings like get_job (single job) and market_stats (aggregate stats) without needing to open any schema.

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 establishes a clear geographic scope (Kansas City, KC-based remote) and a live-data source, which helps an agent decide when this tool applies. However, it gives no explicit exclusions and never references alternatives — it doesn't say 'for a single job use get_job' or 'for company details use get_company.' The context implies the right usage but doesn't spell out the decision boundary.

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