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Tron Read Contract

tron_read_contract
Read-onlyIdempotent

Read-only (constant) call against any TRON contract, executed by our own node. TRC-20 helpers balanceOf / allowance / decimals / symbol / name / totalSupply are built in; any other function can be called with a raw selector plus ABI-encoded parameter. No state is changed and no key is involved. When to use: an agent needs an on-chain value without trusting a third-party API - USDT balance of an address, token decimals, an allowance, or any view function. Do not use: to send a transaction (this never writes), or to look up a historical balance. Returns: ok, contract, function, output_type, value (decoded), value_human for 6-decimal tokens, raw, energy_used.

Input Schema

NameRequiredDescriptionDefault
argumentNoTRON address argument (for balanceOf / allowance)
contractYesContract address (base58 or 41-hex)
functionYesbalanceOf | allowance | decimals | symbol | name | totalSupply, or a raw selector like 'foo(uint256)'
argument2NoSecond address argument (for allowance)
parameterNoRaw ABI-encoded parameter hex, for raw selectors
output_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds material context beyond them: execution on the project's own node, no key involved, and a concrete return shape including energy_used. This is genuinely additive rather than restating the annotation.

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?

Front-loads what the tool is before the when-to-use/do-not-use routing, and closes with a returns list. Sentences are dense but each carries new information; nothing is padding.

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?

With no output schema, the description supplies the return fields (ok, contract, function, output_type, value, value_human, raw, energy_used), which is exactly the gap it needs to fill. Call contract, argument conventions, and failure modes are all covered.

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 coverage is 83%, so the schema already documents contract, function, argument, argument2, parameter, and output_type. The description reinforces which TRC-20 helpers exist but adds no syntax or format detail (e.g. hex encoding of parameter) beyond the schema, so baseline 3 applies.

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?

States a specific verb (read), resource (any TRON contract), execution model (constant call on our own node), and scope (TRC-20 helpers built in, raw selectors for anything else). An agent can distinguish this from siblings like tron_get_contract or broadcast_raw_transaction without opening a schema.

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

Usage Guidelines5/5

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

Has explicit 'When to use' with concrete triggers (USDT balance, token decimals, allowance, any view function) and an explicit 'Do not use' clause that routes writes to a transaction tool and historical lookups elsewhere. The alternatives are named, not implied.

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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