excel_audit_calculations

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it explains the tool's purpose, it lacks critical behavioral details: it doesn't specify the output format (e.g., list of cell addresses, report), whether it modifies the worksheet (likely read-only but unstated), error handling, or performance considerations (e.g., time for large worksheets). For a tool with no annotation coverage, this is a significant gap.

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 a single, clear sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the main action and goal, making it easy to understand at a glance. Every word serves a purpose, with no redundancy or fluff.

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 tool's complexity (auditing cells for formula mismatches), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., a report, error list, or modified worksheet), how results are presented, or any behavioral constraints. For a tool with three parameters and no structured output information, more context is needed to guide effective use.

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 description mentions 'worksheet' and 'suspicious patterns' implicitly, but adds minimal semantic value beyond the input schema. With 67% schema description coverage (two parameters have descriptions, one does not), the baseline is 3. The description doesn't elaborate on parameter usage, such as how patterns are matched or what 'check numeric cells' entails in practice.

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 specific action ('audit a worksheet') and the precise goal ('find cells that should contain formulas but have hardcoded values'). It distinguishes itself from sibling tools like 'excel_validate_formulas' or 'excel_get_formulas' by focusing on detecting mismatches between expected formulas and actual hardcoded values, rather than validating existing formulas or retrieving them.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the workbook must be open), compare it to similar tools like 'excel_validate_formulas' for formula checking, or specify scenarios where this audit is particularly valuable (e.g., compliance reviews or error detection).

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