fda_drug_ndc

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds useful context about data volume (132K+ records) and the content of each entry (product data, active ingredients, packaging info, openfda annotations). It does not contradict annotations and provides additional behavioral hints.

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 and front-loaded, starting with the core purpose, then explaining what each entry contains, and finally providing practical examples. Every sentence adds value, and the examples are essential for a search tool with a complex query language. No fluff or repetition.

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 search syntax, data content, and even mentions count fields. It does not explain what happens if the search parameter is omitted (since it is optional), nor does it describe the response format, but the output schema is absent, and the description gives enough context for an agent to understand the data shape. Minor gaps keep it from a 5.

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 100%, so the baseline is 3, but the description adds significant value by enumerating specific searchable fields (brand_name, dea_schedule, dosage_form, active_ingredients.name, finished) and giving realistic query examples. This goes well beyond the generic syntax in the schema and helps the agent construct correct queries.

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 searches the NDC Directory for drug products, listing the specific searchable fields (brand name, generic name, dosage form, DEA schedule, pharmacological class) and providing concrete examples. It distinguishes itself from sibling FDA tools by focusing on NDC product listings, making its purpose 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 gives strong context on what the tool is for and how to use it via examples, but it does not explicitly state when to use this tool over alternatives like fda_drug_labels or fda_drug_counts. However, the specificity to NDC Directory makes the intended use clear without needing exclusions.

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