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Glama

Record a notebook entry

record_entry

Records a farm task in the field notebook with an audit trail. Requires a write-scoped key and user confirmation; only adds new entries, not for official submission.

Instructions

Register a task in the farm's field notebook (needs a key with write scope). The entry is attributed to the key owner and marked as written by API in the audit trail; the server stores when it arrived and rejects future dates. It only adds new entries: it never edits or deletes existing ones. Confirm the farm, parcel, product and date with the user before calling it. Official submission to the administration is never done here: it needs a person's session in the app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitNoUnit, e.g. 'L/ha', 'kg', 'mm'
titleYesShort title, e.g. 'Tratamiento · Azufre mojable'
farm_idYesFarm id from list_farms
event_atYesWhen it happened (ISO 8601 with offset)
quantityNoQuantity applied
crop_codeNoEPPO crop code, e.g. OLVEU
cost_centsNoCost in euro cents
entry_typeYesKind of task
safety_daysNoPre-harvest interval in days
product_nameNoProduct or input used
parcel_refcatYesCadastral reference of the parcel
treated_area_haNoTreated area in hectares
registration_numberNoOfficial registration number of the product (fito)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare the safety profile (not readOnly, not idempotent, non-destructive), and the description adds substantial context beyond them: it needs a write-scoped key, entries are attributed to the key owner and marked API-written in the audit trail, the server timestamps arrival, future dates are rejected, and it is strictly additive (never edits or deletes). This is exactly the behavioral disclosure a mutation tool needs.

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?

Purpose and the write-scope requirement are front-loaded, and the remaining sentences are informative rather than filler. It is slightly long at five sentences, but each one carries a distinct constraint (attribution, timestamping, add-only, confirmation, submission boundary).

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

Completeness4/5

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

For a 13-parameter, no-output-schema mutation tool, the description covers the essential behavior: scope requirements, attribution, side effects and the add-only guarantee. Its only real gap is not indicating what the call returns (e.g., the created entry identifier), which would help chaining, but overall it is sufficient to call correctly.

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 the schema already documents all 13 parameters and the enum. The description only indirectly highlights farm, parcel, product and date as the values to confirm, without adding format or meaning beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 and resource: 'Register a task in the farm's field notebook.' This clearly distinguishes it from read-oriented siblings like list_entries and entry_history, and an agent knows exactly what the call produces without opening the schema.

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?

Gives real usage context: 'Confirm the farm, parcel, product and date with the user before calling it,' and clarifies the boundary that official administration submission is done elsewhere, in a person's app session. It stops short of naming a sibling tool as the alternative, but the when/when-not framing is explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.