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

Annotations already establish a safe read-only, non-destructive profile, so the bar is lower. The description adds genuinely useful behavior beyond that: available metric series vary by network, so callers should request a range and handle a variable response rather than assuming a given metric exists. This is real, non-obvious disclosure.

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 tightly written sentences with the core purpose front-loaded and the operational caveat immediately after. No filler, no redundancy, and every clause carries information an agent needs.

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 read-only metrics tool with no output schema, the definition covers purpose, the range-based call pattern, and the network-dependent variability of results. It stops short of describing response shape or pagination, but with annotations carrying the safety profile and 80% schema coverage, little is missing for correct invocation.

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 80%, so the schema already documents most parameters including the from_date/to_date range defaults. The description reinforces the range concept but adds nothing about the 'names' filter or why id_organization matters, so it neither compensates for nor exceeds the schema.

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?

It states a specific resource (follower metrics for one connected account) and a specific temporal scope (movement over time), so an agent knows exactly what it retrieves. It does not explicitly differentiate itself from near neighbors like get_publication_stats or get_dashboard_summary, so it falls just short of a 5.

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 line 'ask for a range and read what comes back rather than assuming a metric is there' gives real operational advice about how to call the tool. However, it never says when to prefer this tool over siblings such as get_dashboard_summary or get_publication_stats, so routing guidance is only implied.

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