qc_response_distribution_shift

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

No annotations are present, so the description carries the full burden. It only says 'Compare response distributions', which weakly implies a read-only analysis, but it does not disclose that the tool flags percentage-point or z-score differences, excludes missing/threshold-failing groups, requires a Tabular export, or returns findings, recordsExcluded, and methodologyVersion. The schema's x_suso_qc metadata contains some of this, but the prose description itself does not.

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?

One sentence with no filler besides a redundant tool-name prefix; the substantive clause is front-loaded. It is compact, but it sacrifices useful behavioral information, so the space is not used to maximum effect.

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 has 8 parameters (0 required), nested objects, and no output schema, yet the description explains almost none of the invocation contract. The x_suso_qc block provides methodology and output shape, but the agent is left to infer how 'plan', 'rules', 'thresholds', and 'export_path' should be populated.

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 50%, and the description adds a little meaning by suggesting that 'variables' will include grouping dimensions (interviewer, date, area, version) plus target variables. It does not help with the undocumented parameters ('plan', 'profile', 'confirm_plan_id', 'questionnaire_identity') or with the nested 'rules'/'thresholds' structure, so it only partially compensates for the coverage 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 uses a specific verb ('Compare') and a concrete object ('response distributions'), and it names the comparison dimensions—interviewers, dates, areas, versions—so an agent can tell what the tool analyzes. It does not explicitly contrast it with the many sibling QC tools, and the leading 'qc_response_distribution_shift:' prefix merely repeats the tool name.

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?

There is no guidance about when to choose this tool over the sibling QC tools or which input combination is required. The phrase 'across interviewers, dates, areas, or versions' only implies a use case; it does not state exclusions or alternatives, so an agent receives no selection help.

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