get_client_information

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, which aligns with the description. The description adds behavioral context beyond the annotations by specifying the exact data categories read and warning that 'full' detail should be used sparingly, implying potential performance or data volume implications. This is valuable supplementary transparency.

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 two sentences, front-loaded with the action and resources, and the second sentence provides a concise operational hint. Every word earns its place with no redundancy or filler.

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 read-only tool with rich annotations, the description gives a reasonable overview of the data returned. However, it lacks clarity on when to use this tool versus closely related siblings (e.g., describe_client_catalog, get_client_catalog_status), and does not explain output structure or what 'FYI information' or 'prepared allocations' entail. This leaves some contextual gaps for an agent deciding between tools.

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 description coverage is 0%, so the description must compensate. It implies the client_id parameter via 'selected client' and hints at detail_level through 'Use full only when necessary', but it does not explicitly define valid detail_level values (e.g., 'summary' vs 'full') or explain the semantics of client_id further. This partial clarification adds some value but does not fully bridge the schema gap.

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 reads a selected client's FYI information, Xero templates, and prepared allocations, using the specific verb 'Read' and identifying distinct resources. It does not explicitly name sibling tools or differentiate itself, such as noting when to use get_client_catalog_status instead, so it stops short of a 5.

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 no guidance on when to use this tool versus alternatives, only a note about using 'full' detail level when necessary. This is a parameter-level hint rather than a tool-selection guideline, and no exclusions or alternative tool names are mentioned.

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