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find_alternatives

Find 2-3 safer food or skincare alternatives for a flagged product. Filter by condition lens, get quality scores and ingredient check.

Instructions

Find 2-3 safer swaps for a flagged product: same-category products that rate good/excellent on Clarity's general food/skincare quality score AND contain no ingredient flagged for the given condition lens. Seed by barcode (preferred — e.g. right after scan_barcode flags something) or product_name. Each alternative carries its score, ingredient-recognition coverage, and human_url. The score is a GENERAL quality score, not a condition verdict — verify a chosen alternative with scan_barcode or check_stack. Food and skincare only (supplement swaps are declined honestly for now).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lensNoCondition lens for the ingredient screenall
countNoHow many alternatives to return (1-5)
barcodeNoUPC/EAN of the product to swap away from (6-14 digits)
product_nameNoProduct name to seed from when no barcode is available
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that the score is a general quality score (not condition verdict), returns up to 5 alternatives (though description says 2-3, slight inconsistency), and includes score, coverage, and URL. Does not mention error handling or rate limits, but for a read-only tool it is largely adequate.

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 concise (5 sentences), front-loaded with the main action. Each sentence adds essential information without redundancy. Achieves clarity efficiently.

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?

No output schema, so description compensates by detailing response fields (score, coverage, URL). It also provides guidance on verification. However, it lacks mention of error cases (e.g., no alternatives found). Overall fairly complete for a tool with moderate complexity.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. Description adds value by explaining that barcode is the preferred seed, product_name is a fallback, and clarifies the lens parameter as 'condition lens'. This enhances understanding beyond schema.

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 clearly states the tool's purpose: find 2-3 safer swaps for a flagged product. It specifies the domain (food/skincare), criteria (good/excellent score, no flagged ingredient for condition), and seeding methods (barcode or product_name). It distinguishes from siblings by referencing related tools (scan_barcode, check_stack).

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

Usage Guidelines5/5

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

Explicitly states when to use: right after scan_barcode flags something, or via product_name. It notes that supplement swaps are not supported and advises verifying chosen alternatives with scan_barcode or check_stack. Provides clear context for usage.

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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