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pedronahum

JACTUS MCP Server

by pedronahum

jactus_validate_attributes

Validate contract attributes to catch errors before simulation. Checks required fields, value validity, and type correctness, returning field-level errors and warnings.

Instructions

Validate contract attributes for correctness before simulation.

Checks that all required fields are present, values are valid, and types are correct. Returns field-level error messages and warnings for unknown fields. Call this before jactus_simulate_contract to catch errors early.

Args: attributes: Contract attributes dictionary to validate. Should include contract_type, status_date, contract_role, and type-specific fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
attributesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool checks required fields, valid values, correct types, and returns field-level error messages and warnings for unknown fields. It also implies no side effects (read-only validation). Could mention auth or rate limits, but acceptable.

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 concise with 5 sentences, each serving a purpose. First sentence gives main purpose, then explains checks, return values, usage, and parameter documentation. No wasted words, front-loaded.

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?

Given the tool's simplicity (one parameter, validation purpose), the description covers what it does, when to use it, what it returns, and parameter expectations. Output schema likely covers return structure, so no need for more detail. Complete for context.

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 input schema for 'attributes' is generic (object with additionalProperties). The description adds meaning by specifying expected fields like contract_type, status_date, contract_role, and type-specific fields. Schema coverage is 0%, so description compensates well, though not exhaustive.

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?

The description clearly states the tool validates contract attributes for correctness before simulation. It uses specific verb 'validate' and resource 'contract attributes'. It distinguishes from siblings by mentioning it should be called before jactus_simulate_contract.

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?

The description explicitly advises calling this tool before jactus_simulate_contract to catch errors early. This provides a clear usage context, though it does not mention alternatives or when not to use it.

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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