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

Annotations are sparse (only hints, no side-effect detail), so the description carries the full burden. It discloses that activation spends quota and takes real LinkedIn actions, that a play without a live seat stays a draft, that autonomy rules default to human-wait, and that certain lanes are refused if misconfigured. This is far beyond annotation coverage and is unambiguous.

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?

Despite its length, every sentence is functional: it states the purpose, the single-call nature, and then three numbered rules that prevent common mistakes. The structure (rules and defaults) is easy to parse, and nothing is redundant with the schema.

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?

The description covers the main behavioral constraints, default values, and dependencies across parameters, and it even hints at the return value (the cockpit link). For a complex tool with nested objects and no output schema, this is thorough. Minor omissions like exact error messages or partial-success semantics are acceptable given the detail provided.

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 each parameter has its own description. The tool description adds cross-parameter meaning: the three server-side rules link activate, seat, autonomy, and sources; it explains that dailyCap is ACCOUNT-level and that autonomy only applies to named rungs. This goes beyond what the schema states individually, so it adds genuine value above the baseline.

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?

The description opens with a precise verb and object: 'Create a fully-configured play in one call' and then enumerates the full scope (product, ICP, sourcing lanes, autonomy, caps). It clearly differentiates from update/read tools by implying creation of a new play, and the extensive list of sibling tools makes the distinction obvious.

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?

The description gives strong contextual guidance: it explains when activation should be left to the human (default false), that a live seat is required, and which lanes need their own seeds. It stops short of explicitly naming alternative tools like gtm_update_play, but the intent is clear enough that an agent would not confuse creation with modification.

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