get_matters_table

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns codes in a list format and that they are intended for a specific filter. However, it does not describe if the data is static or dynamic, or any side effects. Given the simplicity (0 parameters), a 4 is appropriate.

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 with no wasted words. It front-loads the purpose and then provides cross-tool context. Every sentence serves a clear function.

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?

The tool is simple: no parameters, no output schema. The description effectively communicates what it returns and how to use the result with a sibling tool. This provides complete guidance for an AI agent.

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 contains no parameters, and schema description coverage is 100%. Per the rules, 0 parameters gives a baseline of 4, and the description adds no parameter info because none exist. The description is fully adequate without needing to explain parameters.

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 retrieves a list of subject matters/topics with their codes, using specific verbs and resource. It distinguishes itself from sibling tools by explicitly referencing its use with search_legislation's matter_code filter.

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 explicit usage context: it tells the agent when to use this tool (to get codes for search_legislation) and implies when not to use it (for other filters). No alternative tools are mentioned but the connection to search_legislation is clear.

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