kubik-tools

Log Pack Observation

log_pack_observation

Logs a real, observed consolidation pack -- "these articles, at these quantities, actually packed onto N pallets at these dims/weight" -- against an existing consolidation group in your team's Library. This is ground truth: it becomes a new data point resolve_quantities and the app's own resolve flow learn from (PRINCIPLES.md P-13).

Two-step by design: call once WITHOUT confirm to preview exactly what would be logged; call again with confirm=true and the preview_id to actually log it. A confirmed log can be undone within 15 minutes via undo_change -- after that it's permanent (append-only ground truth, by design -- see PRINCIPLES.md P-17/P-18 for why).

On the confirm call, only api_key, confirm, and preview_id are actually read -- every other field is required by the schema for shape-consistency but ignored if resupplied, since the values captured during the preview call are what gets logged; to change any of them, call again without confirm for a fresh preview.

Do not use this for a single article's own packing history outside a consolidation group -- that data comes from the app's own data entry, not this tool. Do not use this to correct a mistaken past observation after the 15-minute undo window -- log a new, correct observation instead; past ones are never edited. Requires an EXISTING consolidation_groups id -- this tool cannot create a new consolidation group.

Requires an existing consolidation_groups id (from the app's Consolidation Groups screen) and each member article's number (resolved to its profile automatically).

Input Schema

TableJSON Schema

Name	Required	Description
`api_key`	Yes	Your team's kubik.tools MCP API key (kubik_mcp_...). Required.
`confirm`	No	Set true, with preview_id, to actually log the observation after reviewing the preview. Omit or false for a dry-run preview only.
`width_cm`	Yes
`height_cm`	Yes
`length_cm`	Yes
`weight_kg`	Yes	Total gross weight, in kg.
`preview_id`	No	The preview_id returned by the first (unconfirmed) call. Required when confirm=true.
`pallet_count`	Yes	Number of pallets this pack used.
`member_quantities`	Yes	The articles and quantities actually packed together, e.g. [{article_number: 'MLB1001', qty: 3}].
`consolidation_group_id`	Yes	The id of an existing consolidation group in your team's Library. Required.

Schema Changelog

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

AddedJul 20, 2026
RemovedJul 19, 2026
AddedJul 19, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations are all false/neutral, so the description carries the full burden of behavioral disclosure. It richly describes the two-step design, the confirm-call field-ignoring behavior, the 15-minute undo window, append-only permanence, and the fact that it cannot create a new group. 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.

Conciseness5/5

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

The description is long but every sentence earns its place: it starts with the core function, then the workflow, then field semantics, exclusions, and prerequisites. It is well-structured and information-dense without waste, appropriate for a complex tool with 10 parameters and a two-step flow.

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?

For a tool with 10 parameters, no output schema, and non-trivial behavioral rules, the description covers purpose, flow, field roles, undo/persistence behavior, exclusions, and prerequisites. The only minor gap is the exact preview response shape, but the description indicates what the preview is for and returns preview_id, which is sufficient for the agent to use the tool correctly.

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 70%, and the description adds meaningful context by explaining which fields are read on confirm (api_key, confirm, preview_id), showing an example for member_quantities, and clarifying preview_id's role. The three dimension params (length_cm, width_cm, height_cm) lack individual descriptions, but their names and units are self-explanatory and the description refers to 'dims/weight', so the meaning is adequately conveyed.

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 opens with a specific verb+resource: 'Logs a real, observed consolidation pack...against an existing consolidation group in your team's Library.' It clearly distinguishes this from sibling tools by stating it produces ground-truth data for resolve_quantities and explicitly says 'Do not use this for a single article's own packing history' and 'Do not use this to correct a mistaken past observation,' making the purpose unambiguous.

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 gives explicit when-to-use context ('real, observed consolidation pack'), prerequisites (existing consolidation_groups id, article numbers), and when-not-to-use exclusions (single-article history, post-undo corrections). It also explains the two-step preview/confirm flow and references alternatives like undo_change, providing complete 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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