qc_heaping_round_numbers

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the core flagging behavior. It does not mention how findings are returned, whether the tool is read-only, threshold default behavior, or exclusions such as missing/categorical values; the schema metadata provides some of this, but the 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?

At one sentence, the description is compact and front-loads the purpose. The repeated tool-name prefix is minor redundancy, but there is no padding.

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 eight parameters, no output schema, and many QC siblings, yet the description omits input requirements, return shape, and required export type. Although x_suso_qc metadata contains an output contract and methodology summary, the free-text description alone is not enough for an agent to invoke the tool correctly.

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 coverage is 50%: variables, thresholds, and export_path have inline descriptions, while plan, rules, profile, confirm_plan_id, and questionnaire_identity are undocumented. The description adds no parameter-level meaning, so it does not compensate for the undocumented half; an agent cannot tell what plan, rules, profile, or confirm_plan_id mean from either source.

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 names a specific verb ('Flag') and a precise resource ('numeric heaping'), with concrete examples ('excessive 0/5/10 endings'). This makes it distinguishable from sibling QC tools like qc_straightlining or qc_duplicate_records without opening the schema.

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?

No explicit guidance is given about when to prefer this tool over alternatives, e.g., when variables are continuous/numeric and suspected of rounding. The examples imply use for round-number detection, but there is no exclusion guidance or relationship to sibling QC checks.

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