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goodrx_get_prices

Find discounted prescription drug prices at nearby pharmacies by entering drug name, dosage, and ZIP code to compare costs and access savings.

Instructions

Get GoodRx discount prices for a drug at nearby pharmacies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drug_nameYesName of the drug
dosageNoDosage (e.g., "10mg")
quantityNoNumber of pills (default: 30)
zip_codeNoZIP code to search near
formNoDrug form (tablet, capsule, etc.)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Get GoodRx discount prices' but doesn't specify whether this is a read-only operation, if it requires authentication, rate limits, error handling, or what the output format looks like (especially since there's no output schema). For a tool with 5 parameters and no annotations, this is a significant gap in transparency.

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 a single, well-structured sentence: 'Get GoodRx discount prices for a drug at nearby pharmacies.' It's front-loaded with the core purpose, avoids redundancy, and every word earns its place, making it highly concise and clear.

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

Completeness2/5

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

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral details (e.g., read-only vs. mutation, error handling), usage guidelines relative to siblings, and output information. While the schema covers parameters well, the description doesn't add enough context to compensate for missing annotations and output schema, making it inadequate for full agent understanding.

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?

The description implies parameters like 'drug' and 'nearby pharmacies' (mapping to 'drug_name' and 'zip_code'), but it doesn't add meaningful semantics beyond what the schema already provides. With 100% schema description coverage, the baseline is 3, as the schema adequately documents all parameters (e.g., 'drug_name', 'dosage', 'quantity', 'zip_code', 'form'). The description doesn't compensate with additional context like parameter interactions or examples.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get GoodRx discount prices for a drug at nearby pharmacies.' It specifies the verb ('Get'), resource ('GoodRx discount prices'), and scope ('for a drug at nearby pharmacies'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from siblings like 'goodrx_compare_prices' or 'goodrx_find_pharmacies', which might have overlapping functionality.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus its siblings (e.g., 'goodrx_compare_prices', 'goodrx_find_pharmacies', 'goodrx_get_coupon', 'goodrx_search_drug'). It doesn't mention prerequisites, alternatives, or exclusions, leaving the agent to infer usage based on the tool name alone.

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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