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fyllepo

qubic-mcp

by fyllepo

query_smart_contract

Query a Qubic smart contract read-only using contract index and input type, receiving base64-encoded response data.

Instructions

Query a Qubic smart contract (read-only). Returns the contract's response data as base64-encoded bytes.

Known contracts: 1: QX (Decentralized Exchange) 2: Quottery (Betting & Oracles) 3: Random (Random Number Generation) 4: QUTIL (Utility Functions) 5: MLM (My Last Match - Gaming)

This is a low-level query tool. Use inputType to specify which contract function to call, and inputHex for the function parameters (hex-encoded bytes). If unsure about parameters, start with inputType=0 and empty input to get contract info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputSizeNoSize of input data in bytes (default: 0)
inputTypeYesFunction input type ID (contract-specific)
requestDataNoBase64-encoded input data for the contract function (default: empty)
contractIndexYesSmart contract index (1=QX, 2=Quottery, 3=Random, 4=QUTIL, 5=MLM)
Behavior3/5

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

The description explicitly states 'read-only' and that it returns base64-encoded bytes, which is useful given there are no annotations. However, it introduces an inconsistency by mentioning 'inputHex' while the schema's parameter is 'requestData' (base64), which could confuse an agent about the actual input format.

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

Conciseness3/5

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

The description is well-structured with a numbered list of known contracts, but that list largely duplicates the schema's contractIndex descriptions. The mention of 'inputHex' adds unnecessary confusion, so it is not fully concise or waste-free.

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?

It covers the return format (base64 bytes), known contract indexes, and provides a starter tip. However, it lacks explanation of inputSize, and the encoding inconsistency (hex vs base64) creates a clear gap. Given no output schema, it's moderately complete but not fully self-sufficient.

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

Parameters2/5

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

Schema coverage is 100% with descriptions for all four parameters, so the baseline is 3. The description adds a helpful tip about inputType=0, but it also mentions a nonexistent parameter 'inputHex', conflicting with the schema's 'requestData' and potentially misleading the agent. This reduces the score.

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?

Clearly states it queries a Qubic smart contract (read-only) and lists known contracts, providing a specific verb and resource. However, it does not explicitly differentiate from the sibling tool 'query_contract', so it loses the fifth point.

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

Usage Guidelines4/5

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

Provides clear usage guidance: it labels the tool as low-level, instructs to use inputType for function selection, and suggests starting with inputType=0 and empty input to get contract info. This gives practical direction, though it does not discuss alternatives or exclusions.

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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