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Set calibration offset

set_maintenance_offset
Idempotent

Record how far a maintenance job moved the reference, on an entry that opened a calibration epoch. Takes an ENTRY, not a piece of equipment: the offset belongs to the event that caused it, which is what lets several of them compose for a recipe locked before all of them. Zero is a legitimate measurement and means "measured, and it had not moved" — omit offset_value entirely to clear it back to unmeasured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoHow it was arrived at: pull, counted, or typed
entry_idYesThe maintenance entry that opened the epoch, from list_grinders
evidenceNoOne line recording what it rested on, e.g. "Reference pull 1.38 g/s against 1.74 g/s locked."
offset_valueNoClicks to ADD to a pre-clean reading to get the same grind today, signed along the collar's own number direction. 0 records "unchanged"; omit to clear the measurement

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
entryYes
messageYes

Schema Changelog

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

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

The description discloses subtle behavioral semantics that are not visible in the annotations: zero means a legitimate measurement of no movement, while omitting offset_value clears the measurement to unmeasured. It also explains how multiple offsets compose for a recipe locked before them. These are precisely the kinds of non-obvious behaviors an agent needs to invoke the tool correctly.

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?

Three sentences, each carrying distinct information: the core action, the entry-not-equipment distinction with its compositional rationale, and the zero-vs-clear edge-case. The second sentence is dense and somewhat complex, but the complexity mirrors the domain nuance. Front-loading the purpose works well.

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?

The description, together with the 100%-covered schema and output schema, gives an agent everything needed to call the tool correctly: the object type, the meaning of the parameter values, how to handle zero and clearing, and why the abstraction exists. The annotation set covers idempotency and non-destructiveness, so no safety-relevant behavior is left unstated.

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 description coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by clarifying the critical semantics of offset_value (0 vs omitted) and reinforcing that entry_id refers to an entry, not equipment. It does not add detail for source or evidence beyond what the schema already states, so the score remains 4 rather than 5.

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 and resource: 'Record how far a maintenance job moved the reference, on an entry that opened a calibration epoch.' It clearly differentiates the target ('Takes an ENTRY, not a piece of equipment') from siblings that operate on equipment, so an agent can distinguish set_maintenance_offset from tools like set_grinder_position.

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

Usage Guidelines4/5

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

The description gives clear context for when to use this tool: recording offsets for maintenance entries that opened calibration epochs, and explains why the entry-centric semantics matter for composing recipes locked earlier. It does not name specific alternative tools or state explicit when-not-to-use conditions, but the entry-versus-equipment distinction serves as a strong routing signal.

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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