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Recall Kitchen

search_product_recalls_by_upc

Read-onlyIdempotent

Search recalls by UPC/EAN or a barcode image URL/data URI/MCP image content. Matches extracted recall UPCs first. Returns found=false when the UPC is unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
upcNoUPC or EAN barcode digits
urlNoalias for image_url
limitNonumber of recalls to return, 1-100, default 3
offsetNonumber of recalls to skip
barcodeNoalias for upc
image_urlNooptional HTTPS URL or data:image/...;base64 URI of a barcode image

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
upcYes
hintNo
foundYes
matchNo
offsetYes
productNo
recallsYes
confidenceNo
nextOffsetNo

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context beyond those annotations: 'Matches extracted recall UPCs first' and 'Returns found=false when the UPC is unknown.' This helps an agent predict matching priority and failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. It front-loads the core purpose and immediately adds high-value behavioral details, earning every word.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only, 6-parameter tool with a full input schema and an output schema present, the description covers the essential invocation context: input forms, matching behavior, and unknown-UPC result. The only notable gap is the lack of explicit differentiation from the image-searching sibling tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all six parameters. The description adds a small amount of context by clarifying that UPC/EAN, barcode image URL, data URI, and MCP image content are valid inputs, but it does not add meaningful detail beyond what the schema captures.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Search recalls by UPC/EAN or a barcode image URL/data URI/MCP image content.' It clearly scopes this tool to UPC/EAN-based lookup, which distinguishes it from sibling tools like search_recalls_by_identifier and search_product_recalls_from_image.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: when the caller has a UPC/EAN or barcode image. However, it does not explicitly compare against alternatives, especially search_product_recalls_from_image, which also appears to accept image content, so an agent may be unsure which image-capable tool to invoke.

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

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TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct roles, and the descriptions explicitly separate product lookup from recall search. However, the multiple recall search entry points (by query, UPC, image, and identifier) overlap enough that an agent could pick the wrong one without carefully reading the details.

Naming Consistency5/5

Tool names consistently follow a snake_case verb_noun pattern such as add_, list_, remove_, search_, get_, create_, revoke_, and mark_. The single-word signup is the only minor deviation, but it does not undermine the overall naming system.

Tool Count3/5

At 19 tools, the set is in the borderline-heavy range. The count is justified by the multiple subdomains like API key management, inventory, watch patterns, notifications, and recall searching, but it still feels slightly above the ideal well-scoped tool surface.

Completeness4/5

Core recall search, product lookup, inventory tracking, watch pattern management, notifications, and API key lifecycle are all covered well. Minor gaps exist such as no way to update a watch pattern or view account usage limits, but agents can generally work around them.

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