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get_token_allowance_evm

get_token_allowance_evm

Check the approved spending limit of an ERC20 token for a specific spender on the VeChain blockchain, returning the amount in base units.

Instructions

Get the allowance of an ERC20 token for a spender (returns amount in base units)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenAddressYes
ownerYes
spenderYes
Behavior2/5

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

With no annotations provided, the description carries full burden but lacks behavioral details. It mentions the return format ('amount in base units') but doesn't disclose other traits like read-only nature (implied by 'Get'), error conditions, rate limits, or authentication needs. This is a significant gap for a 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?

The description is a single, efficient sentence that front-loads the core purpose and includes key output detail. There is no wasted text, making it appropriately sized for the tool's complexity.

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 no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers the basic purpose and output unit but misses parameter explanations, behavioral context, and usage guidelines. For a 3-parameter tool in a blockchain context, this leaves significant gaps for an AI agent.

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 description coverage is 0%, so the description must compensate but adds minimal parameter semantics. It implies parameters for token, owner, and spender through context but doesn't explain their roles (e.g., 'owner' is the token holder, 'spender' is the authorized address). The description mentions base units but not how parameters relate to this output.

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 action ('Get the allowance') and resource ('of an ERC20 token for a spender'), specifying it returns amount in base units. It distinguishes from siblings like 'approve_token_evm' or 'revoke_token_approval_evm' by focusing on querying rather than modifying allowances, though it doesn't explicitly name alternatives.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to choose this over 'get_token_info_by_ticker' for token data or 'get_balance' for balances, nor does it specify prerequisites like needing token addresses. Usage is implied by the purpose but not explicitly stated.

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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