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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds traits they cannot express: the call is free, it is equivalent to the loomdesk-farm and loomdesk-runner MCP prompts, and the error contract ('an unknown plan returns the first'). This is exactly the extra behavioral context expected when annotations exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads purpose, then use, returns, behavior, and errors in labeled runs, so it is easy to scan. The first sentence is long and semicolon-loaded, and some return-field enumeration is dense, keeping it just short of fully tight.

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

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

With no output schema, the description fully carries the burden by enumerating the return shape (plans[], farmBar, runnerBar, farmRules, runnerRules, prompt, runnerPrompt) and spelling out behavior and errors. An agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the enum values already carry per-plan glosses ('anchor (yield)', 'wide (volume)'), so the schema does the heavy lifting. The description only notes that the plan selects which prompt text is returned ('the plan asked for, as text to follow'), which is marginal added meaning over the schema's default.

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

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

States a specific verb and resource (returns the house's fee-farm playbooks) and enumerates what the payload contains. It explicitly distinguishes itself from plan_build ('Not for real positions') and names market_tokens as its data source, so an agent can place it among siblings 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.

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

Gives a concrete when-to-use ('Use to follow a proven plan instead of guessing; a small model following it does what the house does') and an explicit when-not ('Not for real positions (plan_build)'), with the alternative named. Nothing is left to inference.

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