ShotPulled

Register a scale

register_scale

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Scale name/model, e.g. Acaia Lunar, Timemore Black Mirror Basic 2
`notes`	No	Additional notes
`power`	No	How it is powered or recharged
`depth_mm`	No	Platform depth in mm
`width_mm`	No	Platform width in mm — measure your drip tray
`auto_tare`	No	1 if it zeroes itself when a vessel is set down, 0 if not, null if unstated
`height_mm`	No	Overall height in mm — the dimension that decides whether it fits under a group head
`auto_timer`	No	1 if the timer starts on first flow, 0 if not, null if unstated
`capacity_g`	No	Maximum weight in grams. The cup or portafilter counts against it
`scale_type`	Yes	What the scale is built for: espresso (drip-tray footprint), brew (pour-over platform), dual (both modes), connected (app/controller integration), dosing (gravimetric dispensing), training, bench (high capacity, coarse)
`connectivity`	No	How the scale talks to an app or a machine controller
`resolution_g`	No	Finest published readability in grams. Leave null unless the maker states it
`water_resistance`	No	IEC 60529 ingress code as published, e.g. IPX4, IPX6, IP67, or none
`flow_rate_display`	No	1 if the scale shows live flow rate in g/s, 0 if it does not, null if the maker never said
`resolution_banded`	No	1 when resolution_g only holds in the lowest weight band and coarsens with load — put the ladder in notes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`message`	Yes
`scale_id`	Yes

TDQS

B3.3/5.0

Behavior2/5

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

The description only says 'Register', indicating a write operation, but provides no details on side effects (e.g., duplicate name handling, generated IDs, whether existing records are modified). The annotations (readOnlyHint=false) already signal a mutation, and the description adds little beyond that domain flavor.

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 a single sentence with no filler. 'Register a brewing scale' is front-loaded, and the parenthetical adds a concise definition in just a few words, using the dash efficiently with nothing extraneous.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema and annotations provide complete input documentation and an output schema, so the description does not need to repeat those details. However, the description is very thin on conveying when to select this tool over alternatives and what the registration action implies behaviorally. It is adequate but not rich for a 15-parameter create operation.

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 all 15 parameters are already documented in the schema. The tool description adds no parameter-specific information; the phrase 'weighs the dose and the yield' is domain context, not a parameter explanation. The baseline of 3 is appropriate.

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 uses a specific verb+resource pair ('Register a brewing scale') and adds domain context ('weighs the dose and the yield') that distinguishes this from sibling register_* tools for other equipment. Even without naming a sibling, the resource noun and the role it plays make the target unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use or when-not-to-use guidance is provided. The only sentence states the action and object, leaving the agent to infer from the 'register' verb that this creates a new scale record. No alternatives, preconditions, or exclusions are mentioned.

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

B3.4/5.0

Disambiguation4/5

Most tools target a clearly distinct resource and action, and the list/register/update/set tool families are easy to tell apart. The closest pair is diagnose_preview and diagnose_shot, which are well-described but similar enough in name that an agent could select the wrong one.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent verb_noun pattern (list_beans, register_grinder, update_shot, set_active). Minor exceptions like grinder_math and kb_changelog lack the imperative verb prefix, but they are readable and do not create real confusion.

Tool Count2/5

34 tools is above the 25+ threshold and feels heavy even though the domain is fairly rich. The many parallel list_* and register_* tools for beans, grinders, machines, scales, waters, programs, and recipes could plausibly be consolidated or trimmed without losing core capability.

Completeness3/5

The core shot lifecycle is well covered: log, update, delete, diagnose, and list shots, plus bean registration and maintenance tracking. However, most registered entities lack update/delete tools, and get_rule has no corresponding list_rules tool, leaving some obvious workflow gaps that agents must work around.

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