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Quote how to manufacture something

mu_quote

Ask the MU manufacturing router how a thing could be MADE before you create a product: which supplier(s) can make it, the est. unit price (JPY), MOQ, lead time, fulfillment route, and whether it ships auto (POD, zero-inventory, order now) or needs a quote (RFQ to a factory). Pass kind (a known POD kind like tee/hoodie/rashguard_ls, OR a non-POD kind like gi/loopwheel_sweat/seamless_knit/rashguard_premium) OR a free-text description (e.g. "道着 for a dojo", "a seamless knit sweater") and the router infers the kind. Optional qty, region (e.g. jp/us), budget (JPY/unit). Read-only — creates nothing. No API key required. Options are ranked: buyable-now (auto + in budget) first. If an option's mode is auto, follow up with mu_create_product; if quote, it needs a human RFQ.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qtyNoQuantity (default 1). Used to check each supplier's MOQ.
kindNoProduct kind. POD kinds: tee, tee_white, rashguard_ls, rashguard_black, hoodie, crewneck, sticker, mug, tote, tank, cap, phone_case, long_sleeve_tee, shorts, beanie, leggings, joggers, apron, canvas, metal_print, pillow, blanket, coaster, placemat, journal, mug_black, wine_glass, towel, bottle, mouse_pad, laptop_sleeve, poster, nfc_coin, device, event_ticket, song, zine, video, karaoke_ticket, house, socks, drawstring_bag, beach_towel, fanny_pack, bucket_hat, kids_tee, backpack, flag, printful_custom. Non-POD also accepted: gi, gi_embroidery, loopwheel_sweat, cut_and_sew, seamless_knit, wholegarment, rashguard_premium, aop_edge_to_edge. Omit to infer from description.
budgetNoTarget budget per unit in JPY. Flags options as within_budget / not.
regionNoShip-to / make region, e.g. "jp" or "us". Prefers region-matching suppliers.
descriptionNoFree-text description of what to make (used to infer kind when `kind` is omitted).

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, description fully covers behavioral traits: states read-only (creates nothing), explains output ranking (buyable-now first), discloses that no API key is needed, and describes mode-dependent follow-up actions.

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?

Description is a single paragraph of moderate length. It is front-loaded with purpose and output, but could be slightly more structured. However, every sentence adds value, so the length is justified given the complexity.

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?

Despite lacking an output schema, description explains the returned data (supplier, price, MOQ, lead time, route, mode) and the ranking logic. It also provides complete flow guidance for next steps, making the tool self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 5 parameters have schema descriptions (100% coverage). Description adds extra meaning: for 'kind' lists specific examples and notes inference from description; for 'qty' mentions MOQ checking; for 'budget' flags within_budget; for 'region' says prefers matching suppliers.

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?

Description states specific verb (ask/quote) and resource (manufacturing router). Clearly distinguishes from siblings like mu_create_product and mu_rfq_create by positioning it as a pre-creation step and specifying follow-up actions for auto vs. quote modes.

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 says 'before you create a product' and provides when-not-to-use by describing when to use mu_create_product (if mode is auto) and when to human RFQ (if quote). Also notes read-only nature and no API key required.

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

A4.1/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose; no two tools appear to do the same thing. Even closely related tools (e.g., mu_quote vs mu_rfq_create, mu_preview_mockup vs mu_create_product) are differentiated by read-only vs. action, or draft vs. send.

Naming Consistency5/5

Tool names consistently use snake_case with the mu_ prefix, and follow a clear verb_noun or noun_verb pattern. Groups like mu_gi_*, mu_ship_*, mu_rfq_* maintain internal consistency. No arbitrary or ambiguous names.

Tool Count4/5

The tool count of 28 is on the higher side but appropriate for the breadth of functionality (registration, product lifecycle, manufacturing, shipping, sales, admin). It's well within a manageable range for a comprehensive server.

Completeness4/5

The tool surface covers core workflows comprehensively: registration, product CRUD (with create, update, retire), manufacturing quotes (informational and RFQ with spec drafting), shipping (CSV, tracking, status updates), sales data, and gi-specific management. Minor gaps include lack of store update/delete and product search, but these are not critical for the main use cases.

Resources