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

Annotations already cover the read-only, idempotent, non-destructive safety profile. The description adds meaningful behavioral context beyond that: the manifest is generated dynamically from the running Flask route table and represents the canonical product inventory, which tells the agent the data is live and authoritative.

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?

Two tight sentences with no filler. The primary action is front-loaded, and the second sentence adds authoritative context without redundancy.

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?

For a parameterless read-only tool with rich annotations and clear sibling context, this description fully covers what the tool does, where the data comes from, and why it matters. No critical call-time information 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 there are no parameter semantics to clarify. The description correctly implies a no-argument call that returns the full manifest, and the schema is already complete.

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 names a specific verb ('Return') and a specific resource ('current machine capability manifest generated from the running Flask route table'). It also defines the tool's role as the 'canonical product-inventory authority for MCP discovery,' which clearly distinguishes it from sibling tools like inspect_capability or discover_capabilities.

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 clear context: this is the canonical authority for capability inventory, so an agent can recognize it as the go-to source for a complete machine capability list. However, it does not explicitly state when not to use it or name alternatives with selection criteria.

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