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Get CookUnity Order History with Meals

cookunity_order_history
Read-onlyIdempotent

Retrieve detailed past order invoices with meal information, pricing, and billing breakdown for specific date ranges to review delivery history.

Instructions

Get past order invoices with full meal details, prices, reviews, and billing breakdown for a date range. This is the only way to see what meals were in past deliveries.

IMPORTANT: Always call this tool FRESH when the user asks about past orders or meals. NEVER rely on cached or previously returned data.

Args:

  • from (string, required): Start date YYYY-MM-DD (inclusive)

  • to (string, required): End date YYYY-MM-DD (inclusive)

  • limit (number): Invoices per page, default 10 (max 50)

  • offset (number): Pagination offset

  • response_format ('markdown'|'json')

Returns (JSON): { total, invoices[{ id, date, total, subtotal, taxes, deliveryFee, tip, discount, orders[{ delivery_date, items[{ name, chef, price, calories, rating, review }] }] }] }

Examples:

  • Last month: { from: "2026-01-01", to: "2026-01-31" }

  • Specific week: { from: "2026-02-03", to: "2026-02-09" }

  • All of 2025: { from: "2025-01-01", to: "2025-12-31", limit: 50 }

Error Handling:

  • Auth errors suggest checking credentials

  • Empty results if no invoices in date range

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromYesStart date (inclusive) for invoice range, e.g. '2025-01-01'
toYesEnd date (inclusive) for invoice range, e.g. '2025-12-31'
limitNoNumber of invoices to return (max 50)
offsetNoPagination offset
response_formatNoOutput format: 'markdown' for human-readable or 'json' for structured datamarkdown
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies that this is the only way to see past meal details, includes error handling guidance ('Auth errors suggest checking credentials', 'Empty results if no invoices'), and emphasizes fresh data calls. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (purpose, important note, args, returns, examples, error handling) and front-loaded key information. It's appropriately sized but could be slightly more concise by integrating the 'Args' details into the main text or reducing redundancy with the schema. Every sentence adds value, but the formatting as a bulleted list makes it slightly verbose.

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 complexity (5 parameters, no output schema, rich annotations), the description is complete. It covers purpose, usage guidelines, behavioral context (fresh data, error handling), parameter examples, and return structure. With annotations handling safety and idempotency, and the description adding meal details and data freshness, there are no significant gaps for an agent to invoke this tool correctly.

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 description coverage is 100%, so the schema already fully documents all 5 parameters. The description adds minimal value beyond the schema: it restates that 'from' and 'to' are required date ranges and provides examples, but doesn't explain parameter semantics like what 'offset' means in practice or how 'response_format' affects output. Baseline 3 is appropriate given high schema coverage.

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's purpose with specific verbs ('Get past order invoices') and resources ('with full meal details, prices, reviews, and billing breakdown'). It explicitly distinguishes this tool from siblings by stating 'This is the only way to see what meals were in past deliveries,' differentiating it from tools like cookunity_list_orders or cookunity_list_deliveries that might not include meal details.

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?

The description provides explicit usage guidance with 'Always call this tool FRESH when the user asks about past orders or meals. NEVER rely on cached or previously returned data.' It also implies when to use it (for past orders with meal details) versus alternatives like cookunity_list_orders (which might not include meals) or cookunity_get_meal_details (for current meals).

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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