normalize_data

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

No annotations are provided, so the description must fully disclose behavioral traits. It only says it 'standardizes' formats, but does not mention what happens on invalid data, whether it modifies data in place or returns a copy, or any error handling. For a data transformation tool, this lack of transparency could lead to misuse.

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?

Two sentences that first state the core purpose with examples, then add usage context. No filler words. Every sentence earns its place. Excellent front-loading.

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 purpose and usage context, but lacks information about return value (does it return the normalized array?) and error behavior (e.g., how are invalid inputs handled?). Given the moderate complexity (nested objects, no output schema), this additional information would be helpful for an agent to correctly invoke and process the output.

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 description coverage is 33% (only data and fields have descriptions, target_formats lacks top-level description but subproperties have them). The description mentions formats like dates and phones, which maps to fields, but adds no new meaning beyond the schema. It also doesn't clarify the structure or behavior of target_formats. Baseline at high coverage is 3.

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?

Description starts with 'Standardize common data formats' which clearly names the action and resource, and lists examples (dates, phone numbers, currencies, addresses). It distinguishes from siblings like validate_json_schema, transform_csv_to_json, clean_text, and merge_datasets, which have different purposes.

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?

Explicitly says 'Essential for agents processing user input or scraped data with inconsistent formatting.' This provides clear context for when to use the tool. However, it does not state when not to use it or suggest alternatives, so it misses a small opportunity for fuller guidance.

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