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Custom Blinds Shop

by io.github.CustomBlinds

get_delivery_estimate

Explain the production lead time for a new order. Production takes 5–7 working days, excluding transit times and outside peak seasons. Returns dispatch_date, production_days, and a plain-language summary safe to share with the customer. Never quote a final delivery date. Call this when a customer asks 'when will it arrive?' to give an honest production timeline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_dateNoISO date string of the order placement date (e.g. '2026-05-18'). Defaults to today.

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the output, exclusions (transit, peak seasons), and a safety constraint (not quoting final dates). It does not explicitly state it's read-only, but the 'returns' language implies no side effects. Minor omission: no mention of invalid date handling.

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?

Three sentences, front-loading the core purpose, then detailing output and usage. No filler words; every sentence provides necessary information.

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?

For a simple tool with one optional parameter and no output schema, it lists the return fields and usage constraints. It could mention edge cases (e.g., past order dates) but is generally complete for straightforward use.

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 coverage is 100% and the schema fully explains order_date (ISO date, default today). The description adds no parameter-specific meaning beyond the schema. Baseline 3 is appropriate since the schema does the heavy lifting.

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 states a specific verb 'explain' with a clear resource 'production lead time for a new order', and lists the exact return fields (dispatch_date, production_days, summary). This distinguishes it from siblings like get_order or create_order, which serve different purposes.

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?

Explicitly gives the trigger scenario ('when a customer asks when will it arrive') and includes a clear negative instruction ('Never quote a final delivery date'). This tells the agent exactly when to use this tool vs alternatives.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but search_products and lookup_catalog overlap significantly in filtering by category and dimensions, which could confuse an agent. The three search/filter tools have subtle differences described, but the overlap lowers the score from perfect.

Naming Consistency5/5

All tools use consistent snake_case with verb-noun structure (e.g., cancel_cart, get_product, update_checkout). There is no mixing of conventions, and the verbs clearly indicate the action, making the set predictable and easy to parse.

Tool Count4/5

26 tools is slightly above the typical well-scoped range of 3-15, but the domain of an e-commerce blinds shop with additional services like AR, swatches, and price matches justifies the count. A couple of legacy tools (create_order, submit_enquiry) add minor bloat.

Completeness4/5

The core purchase flow (search, configure, cart, checkout, payment, order tracking) is fully covered. Additional services like AR visualization, swatches, price match, and WhatsApp handoff are present. Missing features like order listing or coupon application are minor gaps.

Resources