Bidit

Create Bidit request

create_request

Creates a draft request from petal_id, region, fields, description, the customer's email and urgency. Invalid or missing values are rejected with isError, naming the allowed options; nothing is saved. On success Bidit emails the customer a confirmation link, and businesses are invited only after the customer confirms. The result has request_id, access_key (a credential for this request, not shown to users), detail_score and suggested_details (optional details that affect pricing). The email demo@justbidit.ai creates a demo request: demo=true, no email is sent and no business is contacted.

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": {
      "petal_id": "<petal_id>",
      "region": "<region>",
      "fields": "<fields>",
      "description": "<description>",
      "email": "<email>"
    },
    "name": "create_request"
  }
}

Input Schema

Name	Required	Description	Default
`email`	Yes	Customer's email, used only to send the confirm link.
`fields`	Yes	Form field values keyed by field name (max 60 fields, 2,000 characters each).
`region`	Yes	Region code from get_request_form.
`urgency`	No		normal
`petal_id`	Yes	Category id from find_category.
`description`	Yes	Short description of the job in the customer's words.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 6, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations declare only the generic write profile (readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false), and the description adds substantial context beyond them: validation failure names allowed options and saves nothing, success triggers a customer confirmation email, businesses are contacted only after confirmation, and access_key is flagged as a credential not to be shown to users. The demo@justbidit.ai branch spells out exactly what is and is not sent.

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?

Five tight sentences, each carrying distinct information — identity/draft scope, failure behavior, side effects, result shape, and demo mode — with the core purpose front-loaded. Nothing is redundant despite the density.

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?

Strong coverage for a mutation tool with no output schema: it describes return fields (request_id, access_key, detail_score, suggested_details) in lieu of an output schema and discloses failure and side-effect behavior. The remaining gap is lifecycle context — it never connects the created draft to submit_request, cancel_request, or update_request.

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?

Schema coverage is 83%, so the schema carries most parameter documentation. The description still adds real meaning by grouping the inputs into the creation contract and, notably, assigning special semantics to the email parameter (the demo address flips the request into demo mode with no email sent) that the schema does not state.

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 and resource ('Creates a draft request') plus the exact input set, and the word 'draft' is the precise qualifier that separates it from the sibling submit_request. An agent can tell what this tool does and which lifecycle stage it occupies without opening the schema.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the description explains effects and the demo-email path but never says when to choose this over submit_request or update_request, nor that a draft must later be submitted. The param descriptions point to get_request_form/find_category for sourcing values, which is helpful but indirect.

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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