list_accessible_customers

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

With no annotations provided, the description carries the full burden. It discloses that the operation returns directly accessible IDs (read-only), implies authentication requirements ('authenticated user'), and clarifies scope limitations. It also adds implementation context about using the Python client library. However, it does not mention potential errors or pagination, though these are partly covered by the output schema.

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?

The description is front-loaded with the main purpose and is generally concise. However, the final sentence about the source and Python client library is arguably extraneous for tool selection/invocation, making it slightly less tight than a perfect 5.

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?

Given the simplicity of the tool (no params, output schema present), the description is complete: it states purpose, usage, alternatives, and how the output connects to other tools. The output schema handles return format details, so no further structural explanation is needed.

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 has zero parameters, so the baseline is 4 per rubric. The description adds semantic value by explaining that the output can be used as a `customer_id` elsewhere, which is helpful for the agent. This goes beyond the empty schema and justifies a score at 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 specific verb and resource: 'Return customer IDs directly accessible by the authenticated user.' It clearly distinguishes itself from the sibling tool list_accounts by noting that MCC managers should use list_accounts for child accounts, making the tool's scope unambiguous.

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?

It explicitly states that the returned IDs can be used as the `customer_id` parameter across all other tools, and provides a direct alternative: 'For MCC (manager) accounts, use list_accounts() to also see child accounts.' This gives clear 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.