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

Annotations already mark this as read-only, idempotent, and non-destructive; the description adds genuine behavioral context beyond those hints: answers are built by cross-referencing documents, log_id is null when no document contains the answer, and verif_space enriches responses with {value, source} items. This gives an agent realistic expectations about edge cases.

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 information-dense but well structured: the core action is front-loaded, the sibling comparison follows, and constraints and return semantics are packed into later sentences without redundancy. Every sentence earns its place.

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 tool with an output schema, no nested objects, and helpful annotations, the description covers everything an agent needs to call it correctly: input limits, space_id origin, behavioral distinction from the sibling, return fields, and the verif_space-dependent output shape. There are no significant gaps.

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%, so the schema already documents api_key, space_id, and questions. The description adds meaning beyond that by explaining that space_id is 'the same one passed as the optional space_id when extracting,' which links this call to other tools and helps the agent select the correct value. The max-question and max-length limits are already in the schema, so the added value is modest but real.

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 uses a specific verb and resource ('Ask up to 5 questions across every document grouped in a knowledge space') and immediately differentiates itself from claix.window_context.ask by emphasizing cross-document comparison. It clearly tells an agent what this tool does and how it differs from its closest sibling.

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 explicitly states when to use this tool ('use it to compare, add up, or reconcile data spread over several files') and contrasts it with the single-document sibling. It also clarifies the required space_id provenance, tying it to the optional space_id used during extraction.

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