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kubik-tools

by io.github.markopolovic

Resolve Prepack Quantities

resolve_prepack_quantities

Resolves an ordered quantity of a CLASS of goods into concrete prepack units (boxes/cartons), using that class's own logged prepack table -- a class-level lookup (e.g. "small metal fittings"), not a single article. Use resolve_quantities instead when you have a specific article number/name.

Check resolution_status first: "resolved" means units/tier are a real answer, safe to use directly. "not_found" means no prepack table matched the search text, or the matched table has no threshold rules logged -- units/tier are both null. Prepack tables never produce "ambiguous" results (unlike resolve_quantities) -- a table either resolves or it doesn't, there is no packaging-family choice to make.

When resolution_status is "resolved", tier is one of: "observed" (an exact match against a real logged threshold), "estimated" (interpolated between two real logged thresholds), or "verify" (extrapolated beyond the highest -- or below the lowest -- threshold ever actually logged for this table; still returns a real number, but flagged as needing a human's eyes before it's trusted).

Requires an MCP API key (Authorization: Bearer ) issued for a kubik.tools team. Looks the prepack table up by its own article_class text within that team's own Library -- never across teams.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYesYour team's kubik.tools MCP API key (kubik_mcp_...). Required.
quantityYesThe ordered quantity to resolve, in whole units of the class. Must be a positive number.
article_class_queryYesFree-text search over the prepack table's own article_class label, e.g. 'small metal fittings' or 'cable ties'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A5/5.0
Behavior5/5

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

Annotations are minimal (readOnlyHint: false, etc.) but the description adds substantial behavioral context: requires API key, scoped to team's library, explains the meaning of resolution_status and each tier (observed/estimated/verify), and explicitly states that prepack tables never produce ambiguous results. This far exceeds what annotations alone provide and fully discloses the tool's behavior.

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?

Though lengthy, every sentence serves a purpose: introduces core function, contrasts with alternative, explains statuses and tiers, and details auth/scoping. Well-structured into logical paragraphs with no repetition. The density of useful information justifies the length.

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 there is no output schema, the description does an excellent job explaining what the tool returns (units/tier when resolved, nulls when not_found) and what each tier means. It also covers edge cases (verify for extrapolation) and team scoping, making it fully complete for a tool of this complexity.

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?

Schema description coverage is 100%, but the description still adds meaningful semantics by explaining that article_class_query is a free-text search on the prepack table's label, quantity must be positive, and api_key is required with format. It also clarifies the class-level lookup, which enriches what the schema states.

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 ('resolves') and resource ('ordered quantity of a CLASS of goods into concrete prepack units'), and clearly distinguishes from the sibling tool 'resolve_quantities' by specifying class-level vs article-level. No ambiguity.

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 tells when to use this tool vs resolve_quantities, instructs to check resolution_status first, and explains how to interpret each status. Also clarifies that this tool never returns ambiguous results, contrasting with the alternative. This is textbook usage guidance.

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

A4.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: the freight calculation tools are separated by volume-weight, floor-space, and vehicle-fit outputs, and the Library tools are split into create, search, list, log, resolve, and undo actions. The only mild ambiguity is between resolve_quantities and resolve_prepack_quantities, and between calculate_loading_metres and check_truck_fit, but the descriptions explicitly steer the agent to the right tool.

Naming Consistency5/5

All tool names follow a consistent verb_object pattern in snake_case: calculate, check, create, search, list, log, resolve, undo. Despite some verbs being semantically close, the naming is predictable and internally consistent.

Tool Count5/5

Ten tools is well-scoped for the freight-and-logistics domain the server covers: three calculation/fit tools and seven article-observation/resolution tools. Each tool earns its place, and the set is neither bloated nor too thin.

Completeness4/5

The core workflow is covered: freight calculations, article profile creation/search, packing observation logging, and quantity resolution. Minor gaps remain in lifecycle management—there is no update/delete for article profiles and no MCP tool for creating/list consolidation groups or prepack tables, which pushes some flows back into the external app.

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