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

Beyond the readOnly/idempotent annotations, the description discloses several non-obvious behaviors: metrics are the last stored reading rather than a live fetch, fetchedAt timestamps it, null means the platform does not report that metric, and supported=false means the target is unreadable (no analytics or no post id). These are exactly the gotchas an agent needs to avoid misreading results.

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?

It is long, but front-loaded with the summary-vs-detail structure and then the caveats (null, supported=false, stored vs live), followed by routing. The metric enumeration is listy but each item earns its place by defining the payload shape; nothing is padding.

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?

With no output schema, the description carries the full burden of explaining the return shape, and it does: summary fields, per-platform detail fields, null/supported semantics, and freshness via fetchedAt. An agent can consume the response correctly without further documentation.

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 single parameter is fully documented in the schema (range 1-100, default 20, summary unaffected), so the baseline is 3. The description adds the semantic distinction the schema can't: the summary always covers every published post while only the newest posts are returned in detail, which is what makes 'limit' meaningful.

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 opening sentence names the resource precisely ('Metrics for this workspace's published posts') and the body enumerates exactly what is returned: a cross-post summary plus per-platform detail entries. It is immediately distinguishable from list_posts, get_post, and get_link_in_bio, which it names explicitly.

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 states the intended question ('Use this to answer whether posts worked') and then gives explicit routing: drafts/scheduled go to list_posts, single-post detail to get_post, link-in-bio visits to get_link_in_bio. This is a textbook when-to-use / when-not-to-use block.

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