fill_tam_sheet

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

With no annotations, the description fully discloses side effects: only yellow input cells on segment rows are written, blue subtotals/grey rows/demand-side rows are untouched, class-level NACE codes are resolved and flagged, and dry_run returns a plan while actual write returns a summary. This is exemplary transparency for a mutation tool.

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 well-organized: a concise summary paragraph followed by a detailed Args bullet list. Every sentence provides useful information and avoids redundancy. Though longer than typical MCP descriptions, the complexity of the tool justifies the length, and the structure keeps it scannable.

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 description covers the complete workflow, safety mechanisms (dry_run, overwrite warning), edge cases (class-level NACE resolution), and return values (plan or write summary plus plan). With an output schema present, the input side is fully specified. This is a complete and self-contained description for a complex 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?

The schema has 0% description coverage, so the description completely takes over documenting all six parameters. Each parameter is explained with defaults, examples, and special conditions (e.g., output_path overwrite warning, dry_run behavior, exclude_micro meaning). This adds immense semantic value beyond the raw schema.

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 specific action: reading NACE codes from the TAM workbook's 'Company Counts by Segment' sheet, pulling Eurostat counts, and writing to columns F and G. This distinguishes it from sibling tools which are all read-only getter tools; this is the write/fill operation.

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?

Provides strong usage context: dry_run default allows auditing before committing, warns against overwriting the original unless intended, and explains parameter behaviors. It does not explicitly name alternatives, but the sibling context makes it clear this is the only write tool. The guidance is practical and cautionary.

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