add_ibcs_variance_measure

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

With no annotations, the description carries the transparency burden and delivers by explaining the exact formulas for abs and rel, the expected base measure naming convention, and the effect of applyIbcsFormat. It does not cover error handling, overwrite behavior, or permissions, but the core computation and key assumptions are disclosed.

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 exceptionally concise, with three sentences that each add essential information: purpose, formulas, and naming/format expectations. No filler or redundant content; it is well-structured and front-loaded with the primary action.

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?

For a 7-parameter tool without an output schema, the description covers the main decision points and algorithmic behavior. It does not mention return values or edge cases (e.g., missing base measure), but given the complexity and the provided schema, the description is sufficiently complete for correct invocation in most scenarios.

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 schema already describes most parameters, but the description adds meaningful semantics beyond the schema: it defines the kind formulas, explains the '<actual> <comparison>' naming convention for the base measure, and clarifies that applyIbcsFormat adds a leading sign. This goes well beyond the baseline for 86% schema coverage.

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's function: authoring IBCS variance measures against a comparison base (PY, PL, FC). It distinguishes itself from generic measure-creation tools by specifying the variance types (abs/rel) and the IBCS format, making it unambiguous and specific.

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 clear context for when to use this tool: when creating IBCS variance measures with year-over-year or plan comparisons. It does not explicitly name alternatives or state when not to use it, but the specialized purpose and formula details imply the appropriate scenario strongly enough.

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