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Ecommerce Singlecare

ecommerce_singlecare
Read-only

SingleCare prescription coupon prices for a drug: price at each nearby pharmacy (Kroger, CVS, Walgreens, Walmart...) with loyalty price and distance, the lowest price, form, strength and quantity priced, usual retail cash price, generic/brand flag and monthly price history. From singlecare.com's public drug pages via a residential proxy; the pharmacy list depends on the ZIP. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNoOptional 5-digit US ZIP code for nearby pharmacies
drugYesDrug name as in singlecare.com/prescription/<name>, e.g. lipitor, atorvastatin-calcium, amoxicillin

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well past the readOnly/openWorld annotations by disclosing the data source (singlecare.com public pages via a residential proxy), the ZIP-dependent pharmacy coverage limit, and the exact paid-call economics: $0.002 USDC per successful call via x402 on Base/Solana/Arc, with failed calls not charged. The cost and non-charging behavior are exactly the kind of context an agent needs before calling.

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

Conciseness4/5

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

Purpose and returned fields are front-loaded in one dense sentence, with provenance, the ZIP caveat, and pricing in a second. Efficient and well-ordered, though the first sentence is a long comma-chained enumeration.

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

Completeness5/5

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

Covers everything needed for a paid, ZIP-scoped price lookup: what is returned, where the data comes from, how coverage varies, and what invocation costs. With an output schema present and full parameter coverage, no material gap remains for an agent deciding whether and how to call it.

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%, so the baseline is 3, but the description adds real meaning by stating that the pharmacy list (and therefore the result set) depends on the ZIP, which the schema does not say. It also clarifies the drug string maps to singlecare.com drug-page slugs, reinforcing the schema's example.

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?

A specific verb-plus-resource ('SingleCare prescription coupon prices for a drug') with the exact payload enumerated: per-pharmacy price, loyalty price, distance, lowest price, form, strength, quantity, retail cash price, generic/brand flag, and history. This is unmistakably distinct from the retail-catalog siblings in the list.

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?

Usage is implied rather than stated: the description makes clear this is US pharmacy price comparison driven by a ZIP, but it never says when to prefer it over adjacent price tools such as ecommerce_costplusdrugs or ecommerce_chemist_warehouse, nor any exclusions. An agent can infer the use case but must reason about alternatives itself.

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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