surveymonkey_list_responses_bulk

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It discloses useful behaviors such as pagination defaults, the max per_page of 1000, ISO 8601 date formats, the 'simple' format switch, and supported status filters. However, it does not mention authentication requirements, rate limits, or any caveats about large bulk responses.

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 front-loaded with a one-sentence purpose statement followed by a compact, scannable Args list. Every argument line earns its place by providing concrete semantics, defaults, or allowed values, with no filler or repetition.

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 the 10-parameter surface area and no annotations, the description covers the required invocation details well: required survey_id, filtering options, pagination, and date formats. The presence of an output schema means return values need not be described. It falls slightly short only in not explaining when to choose this over the closely related list_responses tool.

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 is the only source of parameter meaning. It comprehensively documents all 10 parameters with types, defaults, allowed values, separator conventions, and date formats, adding substantial value beyond the bare schema titles.

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 opens with a clear verb and resource: 'Lists responses for a survey including all answer data.' This conveys the core purpose and the emphasis on full answer data, though it does not explicitly distinguish itself from the sibling surveymonkey_list_responses or surveymonkey_export_responses_csv.

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 implies usage through the tool name 'bulk' and the phrase 'including all answer data,' but it never states when to prefer this tool over list_responses or when to use an export tool instead. There are no explicit exclusion conditions or alternative routing.

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