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log_bird_batch

Log a new bird inventory census batch. Supports confirm and idempotency validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoOptional notes
farmIdYesThe unique farm ID
confirmNoSet to true to commit, false for dry-run preview
varietyYesThe quail or poultry variety
locationYesCurrent location (Brooder, Grow-out, Layer, Breeder, Other)
quantityYesThe number of birds in the batch (positive finite integer <= 50000)
hatchDateYesThe hatch date (YYYY-MM-DD, cannot be in the future)
idempotencyKeyNoUnique request idempotency key

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, openWorldHint=false, so the safety profile is covered. The description adds only that confirm (dry-run) and idempotency validation are supported, which is also stated in the schema, and leaves unresolved tension with idempotentHint=false (an idempotency key is accepted, yet the call is declared non-idempotent).

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?

Two short sentences with the core action front-loaded and no padding. The second sentence is vague rather than wasteful, so it is efficient but not maximally informative.

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?

For an 8-parameter mutation tool with no output schema, the description omits what a dry-run returns, what happens on validation failure (duplicate idempotency key, invalid hatch date), and confirmation requirements. The rich schema compensates for field-level gaps but not for outcome behavior.

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%, including units, ranges, date format and enum-like location values, so the schema carries the parameter burden and the baseline is 3. The description contributes no additional parameter meaning beyond loosely naming 'confirm' and idempotency.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Log a new bird inventory census batch'), which is clearly distinct from read siblings like get_bird_batches. However, it does nothing to separate itself from the many other write siblings (log_hatch_set, log_candling, log_egg_collections), so it is clear but not differentiating.

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?

'Supports confirm and idempotency validation' hints at capability but gives no when-to-use guidance, no prerequisites, and no routing to alternatives such as log_hatch_set or log_hatch_result. An agent gets no criteria for choosing this tool over its siblings.

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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