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Ranch.Bot MCP Server

Ranch.Bot MCP Server

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by RanchBot

Create ration

create_ration

Creates a named feed ration from a user's recipe with per-head daily amounts and optional group assignments, structure only, no formulation; assignments start inactive.

Instructions

Create a feed ration the user has already decided on: a named recipe in per-head-per-day pounds, optionally assigned to groups. STRUCTURE ONLY — never formulate, balance, or validate nutritional adequacy, and never invent amounts; if asked what or how much to feed, decline and refer the user to their nutritionist. Assignments are created INACTIVE: the user activates them in the app (Rations page) before they appear on the Feed Mode Today board.

Input Schema

NameRequiredDescriptionDefault
nameYesRation name, e.g. "Finishing lambs — winter".
unitNoWeight unit label. Defaults to "lb".
farm_idNoThe ID of the farm (optional if a default is set).
assignmentsNoGroup assignments; created inactive pending in-app activation.
ingredientsYesIngredients in load order (array order = default mixer load order).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only tell the agent this is a non-read-only, non-destructive write. The description adds genuinely non-obvious behavior: assignments are created INACTIVE and require in-app Rations-page activation before appearing on the Feed Mode Today board. That is exactly the kind of side-effect context structured fields do not carry.

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?

Three sentences, front-loaded: purpose first, hard constraints second, lifecycle behavior third. No redundant restatement of the title or schema, and every clause earns its place.

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 5-parameter mutation tool with no output schema, the description covers the identity of the resource, the boundaries of agent behavior, and the activation lifecycle. Nothing an agent needs to call it correctly is missing.

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 and the schema already documents each parameter including nested assignments. The description adds marginal framing (whole object is a 'per-head-per-day pounds' recipe, group assignment is optional) that ties the parameters to the domain, but no new syntax beyond the schema.

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 (create) and resource (feed ration) with the exact shape of the object ('a named recipe in per-head-per-day pounds, optionally assigned to groups'). This is clearly distinguishable from the read siblings list_rations/get_ration, and the domain framing (a 'recipe') removes ambiguity.

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?

Explicitly names the trigger condition ('a feed ration the user has already decided on') and the negative case ('never formulate, balance, or validate... if asked what or how much to feed, decline and refer the user to their nutritionist'). This is textbook when-to-use and when-not-to-use 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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