word_extract_sow_structure

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

Annotations confirm read-only and non-destructive behavior. The description adds value by detailing the return format (dictionary with extracted data) and providing a concrete example, which goes beyond what annotations offer. No contradictions.

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-structured with a clear lead sentence, a brief explanatory paragraph, and an example. It is concise, but the example could be shortened slightly without loss of clarity.

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 simple extraction tool with one parameter and no output schema, the description adequately covers purpose, parameter, example, and return type. No gaps are evident given the low complexity.

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?

With 100% schema coverage, the description merely restates the parameter's purpose ('Path to the SOW document') without adding extra constraints, formats, or examples. Baseline of 3 is appropriate as the schema already does the heavy lifting.

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 it extracts structured data from an existing SOW document, which distinguishes it from siblings like word_cleanup_sow (cleanup) and word_generate_sow (generation). The verb 'Extract' and resource 'SOW document' are specific and unambiguous.

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 mentions the extracted data can be used to generate new documents, but does not explicitly state when to use this tool versus alternatives like word_parse_sow_template. No usage exclusions or prerequisites are provided, leaving the agent to infer context from sibling names alone.

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