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

The annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so 'Read only' adds nothing; however, the description adds a real scope constraint not in the structured data — that the data is Postfjord's own internal numbers, not customer data — which prevents misattribution. With no output schema, the enumerated metric list also usefully describes what comes back, though freshness/aggregation mechanics remain unstated.

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?

Safety/scope marker 'Read only' leads, followed by one dense sentence listing the metrics and a closing scope sentence — well front-loaded with no filler. The metric enumeration is long but each item earns its place because there is no output schema to document the returned fields.

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 zero-parameter, annotation-covered, no-output-schema tool, the definition supplies everything an agent needs: what is returned, at what cadence (per month, per week), and the critical boundary that it is internal plan data rather than customer workspace data.

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 is nothing for the description to disambiguate at the argument level; baseline 4 applies. The description does not need to compensate for any schema gap since the input schema is trivially 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 the exact resource (Postfjord's internal plan metrics toward $1M ARR) and enumerates the specific measures returned: MRR, paying customers, waitlist, new/activated workspaces, attribution source, and branded search volume. The closing clause 'never about a customer workspace' separates it from the many customer-facing analytics/post tools in the sibling set.

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 gives a clear positive context ('For the Postfjord team's plan board') and an explicit exclusion ('never about a customer workspace'), which is the main routing hazard for a metrics tool. It stops short of naming a specific alternative tool to use for customer-workspace numbers, so the agent must infer the sibling to switch to.

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