ai_parser_list

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds transparency about error conditions (missing API key, rate limit, request failure) and return type (JSON array). No contradictions.

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?

Description is well-structured with clear sections, no redundant sentences. Every sentence serves a purpose (what it does, when to use, returns, raises).

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?

Given zero parameters, rich annotations, and an output schema, the description is complete: it covers purpose, usage, return format, and errors. No 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?

Tool has no parameters; schema description coverage is 100% trivially. Description adds value by explaining the return format and behavior, meeting the baseline of 4 for zero-parameter tools.

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 that the tool lists AI parsers on the account and specifies the returned fields (id, name, status, version, generation time). It explicitly distinguishes from the sibling tool 'ai_parser_get_details' which retrieves full details of one parser.

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?

Provides explicit 'When to use' (discovering parsers before reuse) and 'When NOT to use' (getting one parser's full details) with a specific alternative named ('ai_parser_get_details').

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