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

With no annotations, the description must carry behavioral disclosure. It transparently states the partial-update behavior (only provided fields change), the destructive replacement behavior for screening_questions, and the authentication requirement. However, it omits other behaviors like whether the operation is idempotent, how missing fields are treated (implicitly unchanged), or error/response semantics. It covers the most critical nuances but not exhaustively.

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 concise (two sentences) and front-loaded with the core purpose. It packs a lot of essential information efficiently: the operation, partial-update semantics, the screening_questions replacement behavior, and authentication. Every sentence earns its place without redundancy, though the phrasing is dense.

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 14 parameters, a nested screening_questions object, no output schema, and no annotations, the description covers the main usage context and the one special destructive behavior. It does not mention error scenarios, success indicators, or other edge cases, but it addresses the key facts an agent needs to call the tool correctly. It is adequate but not comprehensive for the tool's complexity.

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?

The schema description coverage is 100%, so each parameter is already documented. The description adds global parameter semantics—'Only provide fields you want to change'—which clarifies that omitted fields remain unchanged, a valuable instruction beyond the per-field schema descriptions. This exceeds the baseline of 3 for high coverage.

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 ('Update'), a resource ('existing job posting'), and the platform ('Himalayas'), making the tool's purpose clear. It doesn't explicitly contrast with siblings like create_company_job or delete_company_job, but 'existing' implies a modification operation, which is enough for basic differentiation.

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 guidance about how to use the tool ('Only provide fields you want to change' and the screening_questions replacement rule), but it does not specify when to choose this tool over alternatives (e.g., create_company_job for new jobs, delete_company_job for removal). No explicit when/when-not or alternative routing is given, leaving the agent to infer.

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