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

Annotations already cover read-only/idempotent safety, but the description adds substantive behavior: nothing is self-serve, provisioning is quoted and set up per account, the customer then signs in and picks a package, and the empty-list case returns whether one is enabled versus awaiting setup. That is genuine context an agent cannot derive from the annotations.

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?

Purpose is front-loaded in the first sentence, and the provisioning/empty-state/fallback details all serve an invocation decision. It runs long and could tighten the package explanation and URL, but no sentence is pure filler.

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?

An output schema exists, yet the description still gives enough behavioral and edge-case coverage (not-connected case, missing-system case, next tool to call) for an agent to act correctly. Nothing material to calling or interpreting this tool is missing.

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?

The tool takes zero parameters, so the 4 baseline applies; the schema has nothing to explain. The description adds value by noting the returned id is what every other record tool, including list_automations and propose_automation, consumes — though that is return-value semantics rather than parameter semantics.

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?

Opens with a specific verb and resource ('List systems connected to AI Agents') and immediately scopes it to a signed-in CRM Connector customer's own business systems. It states what is returned (id, package, per-record-type permissions) so it is clearly distinguishable from record-reading siblings.

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?

Explicitly says 'Use first when a signed in CRM Connector customer asks about the records in their own business systems', and gives a fallback path when a system is absent (say so, then send_request with kind ai_access or share the request URL). When-to-use, when-not-in-list, and the alternative are all named.

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