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hydracds

Cardexscan MCP Server

by hydracds

create_otc_offer

Create a peer-to-peer OTC trading offer on Cardexscan and receive an unsigned transaction CBOR plus offer ID for signing and submission.

Instructions

Create a new peer-to-peer OTC trading offer on the Cardexscan marketplace. Returns an unsigned transaction CBOR and offer ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offerAssetYesDetails of the token being offered for sale
offerAmountYesAmount of the offered token (in smallest unit)
allowPartialNoWhether partial fills are allowed (default: false)
requestAssetYesToken requested in exchange. Use 'lovelace' for ADA or a token object
minTakeAmountNoMinimum amount for partial fills (required if allowPartial is true)
requestAmountYesAmount of the requested token (in smallest unit)
walletAddressYesCardano wallet address (bech32 format, starts with 'addr1')
expirationHoursNoNumber of hours until the offer expires (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

B3.3/5.0
Behavior3/5

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

No annotations exist, so the description carries the full behavioral burden. It usefully notes the return is an 'unsigned transaction CBOR and offer ID,' implying the caller must sign/broadcast, but it never states whether the offer goes live immediately, what permissions are needed, or what the signing/submission step entails. Partial disclosure for a mutation tool with zero annotation coverage.

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?

Two tight sentences with zero waste, front-loading the core action and then the return contract. Every sentence earns its place and nothing is padded.

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

Completeness3/5

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

With no output schema the description does cover the return value (CBOR + offer ID), which is helpful. However, for an 8-parameter nested-object mutation tool with no annotations, it omits the post-creation workflow (signing/broadcasting), auth requirements, and lifecycle details, leaving meaningful gaps.

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 8 parameters including the nested asset objects and fields like allowPartial/minTakeAmount. The description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

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 and resource: 'Create a new peer-to-peer OTC trading offer on the Cardexscan marketplace.' The verb 'Create' inherently separates it from siblings like fill_otc_offer, cancel_otc_offer, and get_otc_offers, though no sibling is named explicitly. Purpose is unambiguous but lacks explicit routing language.

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 offers no when-to-use guidance, no prerequisites (e.g., wallet/signing), and never contrasts this with related siblings such as fill_otc_offer or submit_swap. The only usage signal is the implicit 'create an offer' reading of the name, which is left entirely to inference.

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