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Curo: Peptide Research AI Agent with Prices, Stock and Lab Reports (COAs)

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Read-onlyIdempotent

Read shipping, returns, contact, and research-use policies.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is fully covered structurally. The description adds only the content scope (which policies are returned); it doesn't mention freshness, caching, or format of the policy text. Given rich annotations, this is an adequate but modest addition.

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?

A single short sentence that front-loads the verb and enumerates contents with zero filler. Nothing wasted, nothing buried.

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 zero-param, read-only lookup with no output schema, the description adequately conveys what the agent will get back (policy text categories). It could add a note on structure or breadth of the returned policies, but it's essentially complete for this complexity level.

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?

The tool takes zero parameters, so there is nothing to document; baseline 4 applies. The description correctly implies no inputs are needed to fetch store-level policy data.

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?

States a specific verb (read) and enumerates the exact resource contents: shipping, returns, contact, and research-use policies. This is clearly distinct from siblings like get_product or build_cart, though it doesn't explicitly name an alternative. Purpose is unambiguous without reading the schema.

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 enumerated policy categories imply when to reach for it (policy questions about shipping/returns/contact), but there is no explicit when-to-use or when-not statement, and no sibling is named as an alternative. Usage is inferred rather than guided.

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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