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

The description discloses behavioral traits beyond annotations: batch size limit (100), upfront quota check with 402 rejection on overage, all-or-nothing atomicity, return structure, required scope (`trace:record`), fallback behavior without key. Annotations only indicate non-readOnly and non-destructive; the description adds rich operational context. No contradictions.

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 (5 sentences) and well-structured: purpose first, then usage guidance, batch behavior, return format, and auth. Every sentence carries essential information with no fluff. Ideal front-loading of the primary action.

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's complexity (one parameter that is a complex array of objects) and the absence of an output schema, the description fully covers all necessary context: batch limits, quota behavior, return shape, auth requirements, and error handling. It is complete enough for an agent to select and invoke the tool correctly.

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?

Input schema has 100% coverage with descriptions for all fields. The description adds meaning beyond the schema by explaining batch-level semantics (quota check, rejection, atomicity) and cross-referencing the shape of trace_record. It also describes the return format (not present in schema). This adds significant value, though individual parameter details are already covered by schema.

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 clearly states the purpose: 'Write up to 100 Kamy Trace records in one call.' It specifies the verb (write), resource (Kamy Trace records), and maximum batch size. It also distinguishes itself from the sibling tool trace_record by indicating when to use this batch version over the singular one.

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?

Explicit guidance is provided: 'Reach for this over trace_record whenever you have more than a couple of buffered LLM calls to persist' with rationale (one auth, quota check, round trip). It also advises on handling quota exceedance ('split it or upgrade rather than retrying') and mentions auth requirements. This fully addresses when, why, and when not to use the tool.

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