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Create Deal Budget

create_deal_budget

Use this when working with RetailHardHat budgets records in the connected organization. Create a draft deal budget; existing current-budget rules still apply. No change occurs until a human approves the exact request in Settings > MCP and execute_approved_action is called. MCP approval requirements are configurable by the organization administrator; business workflow approvals always apply.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dealId": "<dealId>",
      "data": "<data>"
    },
    "name": "create_deal_budget"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYes
dealIdYes

Output Schema

NameRequiredDescriptionDefault
dataYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: it creates a draft, existing current-budget rules apply, no change occurs until a human approves the exact request in Settings > MCP and execute_approved_action is called, and business workflow approvals always apply. This is exactly the kind of approval-workflow and side-effect information an agent needs.

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 reasonably sized, but the first sentence is generic filler and delays the specific purpose. The approval-workflow sentence is dense but valuable, while the draft/current-budget sentence is appropriately concise.

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

Completeness4/5

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

Given the presence of an output schema and annotations, the description covers the critical approval and draft-state behavior well. However, it does not compensate for the missing parameter descriptions or provide guidance on alternatives, leaving some gaps for a tool with a nested data object.

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%, and the description does not explain the two parameters or the nested data fields (name, notes, unitCount, assumptions, squareFootage). It only implies a deal ID and data payload via the tool's purpose, leaving the agent to rely entirely on undocumented schema property names.

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 specific verb and resource: 'Create a draft deal budget.' The word 'draft' and 'deal budget' distinguish it from related tools like create_site_budget or set_current_deal_budget, though no sibling is explicitly named.

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 opening line, 'Use this when working with RetailHardHat budgets records in the connected organization,' is generic and does not explain when to choose this tool over alternatives such as create_site_budget or apply_budget_template. No when-not conditions or alternatives are provided.

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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