list_annotations_for_call

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

Describes what an annotation contains and clarifies independence from plaintext feature, but lacks behavioral details like pagination, ordering, or auth requirements. Without annotations, some burden is carried, but still gaps.

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?

Four sentences, each purposeful. Front-loaded with purpose, then defines annotations, then use case, then clarifies a nuance. No wasted words.

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?

Explains return fields and usage context, but missing details on pagination, error handling, and explicit mention that it returns a list. Simple tool but could be more complete.

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 only parameter (callId) is well-described in the schema (100% coverage). The description repeats the source ('records[].id from query_calls') which adds no new meaning beyond the 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 verb ('Return') and resource ('annotations attached to an LLM call'), distinguishing it from siblings like list_annotations_by_label (by label) and get_annotation (single annotation).

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?

Explicitly states when to use: 'to check whether a call has human review attached or what past reviews said.' Provides context but does not explicitly mention when not to use or alternatives.

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