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

The description adds substantial behavioral context beyond the annotations: it explains grouping by fingerprint, sorting defects-first, classification of errors into ours/user/unknown, redaction of sensitive data, and scoping rules including admin key behavior. This is rich, non-redundant information that helps the agent understand exactly what the tool does and its limitations. 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 dense but every sentence contributes critical information. It front-loads the core purpose (grouping and sorting) then adds attribution semantics, redaction policy, filtering options, and scoping. Despite its length, there is zero verbosity; each clause earns its place. The structure flows logically from what the tool does to how data is handled.

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 list tool with four optional parameters, the description covers all necessary context: what is returned (grouped rows with hit counts and first/last seen), the classification of sides, redaction of sensitive content, filtering dimensions, read-only and cost implications, and scoping. With no output schema, the description adequately implies the return shape. No critical information for correct invocation is missing.

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 input schema has 100% description coverage for all four parameters, each with detailed descriptions of their meaning and enums. The tool description does not add any additional parameter-specific information; it merely restates filtering options. With high schema coverage, the baseline of 3 is appropriate as the description does not need to compensate but also does not add extra value 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 tool's function: 'list_errors' lists errors recorded against a workspace, grouped by fingerprint, with sorting and attribution. It distinguishes itself from sibling tools like 'error_detail' by describing the grouped, filterable nature of the listing. The verb 'list' plus the resource 'errors' is explicit and unambiguous.

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 contextual guidance (read-only, scoped to workspace, 0 credits) but does not explicitly state when to use this tool versus alternatives. It mentions filtering by surface and kind but does not say 'use this instead of error_detail' or outline specific conditions. The guidance is implied rather than explicit, falling short of the highest bar.

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