Check whether a product, brand, drug, or vehicle has an official US recall or safety alert. Aggregates openFDA (food/drug/device), CPSC (consumer products), and NHTSA (vehicles, incl. VIN decode) into normalized JSON. Deterministic, official sources only — useful as a pre-purchase safety guardrail for shopping agents.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | No | Vehicle VIN | |
| make | No | ||
| year | No | ||
| model | No | ||
| query | No | Product, brand, or drug name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden and discloses key behaviors: aggregates multiple official sources, returns normalized JSON, is deterministic, and uses official sources only. It omits rate limits and error behavior but is still informative for a read-only 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?
Two sentences pack purpose, sources, output format, and use case without redundancy. The main function is front-loaded, and every clause adds value.
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 sources but doesn't explain parameter combinations (e.g., VIN vs query precedence) or the structure of the normalized JSON. Since there is no output schema, these details are missing.
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?
Only 2 of 5 params have schema descriptions (40% coverage), and the description does not fully map product categories to parameters. It mentions VIN decode but not how make/year/model are used together, leaving a gap in parameter understanding.
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 a specific verb ('Check') and resource ('official US recall or safety alert'), enumerating product categories (product, brand, drug, vehicle) and data sources (openFDA, CPSC, NHTSA). It distinguishes itself from the unrelated document-processing sibling tools.
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?
It explicitly positions the tool as a 'pre-purchase safety guardrail for shopping agents,' providing clear usage context. It doesn't state exclusions or alternatives, but none are needed given the sibling tools are unrelated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
All six tools have clearly distinct purposes: converting markdown to different formats, merging/stamping PDFs, and checking recalls. No two tools are easily confused.
Most tools use a verb_noun pattern (generate_pdf, merge_pdfs, watermark_pdf, check_recalls), but markdown_to_docx and markdown_to_html use a different pattern (source_to_target). The inconsistency is minor and still readable.
With 6 tools, the count is reasonable for a document conversion utility. However, the inclusion of check_recalls feels out of place for a server named 'pdf', slightly diluting focus.
The tool set covers markdown-to-PDF and PDF merging/watermarking, but lacks PDF-to-other-format conversion, splitting, or editing. The recall checker is an unrelated gap filler. Core PDF workflows are partially covered.