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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns explanatory text about the system layers and services. However, it does not mention if the tool is read-only, whether it requires authentication, or if there are any rate limits. For a knowledge retrieval tool, the absence of these details is acceptable but prevents a higher score.

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 a single sentence that packs a lot of information: what the tool does, how to get different outputs, and scope of the output. It is front-loaded with the purpose. While concise, it could be slightly clearer with a small break between the two usage modes, but overall it is efficient.

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 tool has one optional enum parameter, no output schema, and no annotations, the description is sufficient for an agent to understand its use. It explains both invocation modes and the scope of results (services within a layer). It does not need to detail return values since they are explanatory text. The description is complete enough for an agent to invoke the tool 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 description coverage is 0%, but there is only one parameter with enum values. The description adds significant meaning beyond the schema by explaining the effect of including versus omitting 'layer'. The enum values are listed in the schema, so no further explanation of each layer is needed. The description effectively compensates for the lack of schema descriptions.

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 clearly states what the tool does: explain the Growthmak Growth Engine System. It distinguishes two distinct use cases: get an overview of all five layers (by omitting 'layer') or get detail on a specific layer (by passing its name). This differentiates it from sibling tools like 'book_growth_audit' or 'find_case_studies'.

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 explicitly tells when to omit the parameter (overview of all layers) and when to pass it (for detail on a specific layer). It does not name alternative tools explicitly, but the context of sibling tools is present and the usage distinction is clear enough for an AI agent to decide between calling this tool with or without the layer, and to know not to use it for auditing or case studies.

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