Get publication stats

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely non-obvious behavior: totals are snapshot at the end of the period, subscribers_churned excludes free unsubscribes because Substack doesn't track them, subscribers_new is derived rather than counted, and revenue_usd is annualized dashboard revenue, not cash received. These are exactly the semantics that would otherwise cause misreporting.

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?

Front-loaded with the metric list, then a definitions paragraph. It's dense but every sentence in the second paragraph corrects a plausible misreading (churn scope, derived new-subscriber count, annualized revenue), so little is wasted. Slightly heavy for a one-parameter read tool.

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?

There is no output schema, so the description must carry return-value semantics and it does so well for the four headline metrics. It doesn't state whether the response contains only those fields or describe the object shape, which is the remaining gap.

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 100% and the enum already documents 7d/30d/90d with a 30d default. The description restates the same options ('7, 30 or 90 days') without adding format or edge-case detail, so it neither helps nor hurts beyond the schema 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 names the exact metric set returned (total and paid subscribers, new subscribers, paid cancellations, estimated revenue) for a time period, so an agent knows precisely what it gets. It doesn't explicitly distinguish itself from close siblings like get_daily_stats, get_audience_insights, or get_post_stats, so sibling disambiguation is left to inference.

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?

Usage is implied by the framing — period-aggregated publication-level stats — but there is no explicit 'use this when you want X, use get_daily_stats instead when you want Y' guidance. For a tool sitting next to four other stats siblings, that omission costs it.

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