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

With no annotations, the description carries the full burden. It does disclose the key behavioral trait — that this is a simulation against a 'fake' context with no real side effects — which is genuinely useful. It says nothing about permissions, rate limits, or what the dry-run returns, so the disclosure is partial.

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?

A single front-loaded sentence with no wasted words. It is efficient, though the terseness borders on under-specification given the complexity of the nested-object inputs.

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 tool with two nested-object parameters, no output schema, no annotations, and 0% schema coverage, a single sentence is inadequate. The agent has no way to know what a valid 'program' or 'context' object looks like, nor what the dry-run reports back.

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 0% and both parameters are untyped nested objects, so the schema provides no guidance. The description maps 'program' to a routing program and 'context' to a scan context, adding minimal semantic value, but says nothing about the required shape or fields of either nested object.

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 action (dry-run/simulate) on a specific resource (a routing program evaluated against a fake scan context). This is clear and distinct from the mutating sibling set_routing. It stops short of explicitly differentiating itself from siblings like render_qr, but the verb+resource is 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?

'Dry-run' strongly implies the usage context (validate routing before applying it), so the when-to-use is inferable. However, the description names no alternative and states no exclusions or prerequisites, leaving the agent to infer the relationship to set_routing or render_qr.

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