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

Annotations already declare readOnly=false, idempotent=true, and destructive=false, so the safety profile is covered. The description adds the non-publishing/non-scheduling boundary and an epistemic constraint on causal claims, which is genuine extra context, but it says nothing about idempotency behavior, permissions, or what happens to existing data.

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?

Three short sentences, front-loaded with the payload definition, followed by two tight constraints. Every sentence earns its place with no filler.

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?

An output schema exists so return values needn't be described, and annotations cover the safety profile. Yet for a 7-parameter mutation with 0% schema coverage and nested variants, the description is thin on parameter meaning and idempotency semantics, leaving the definition only adequately complete.

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 description coverage is 0%, so the description carries the burden; it explains the semantic core (hypothesis, metric, labeled variants with labels/postIds), which is valuable. But brandId, title, idempotencyKey, and minimumPostsPerVariant are left entirely undocumented in both schema and description, leaving a real gap.

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?

States a specific verb (save/create) plus the resource and its payload: a hypothesis, success metric and labeled post variants forming an observational content experiment. An agent can distinguish this from get_experiment/list_experiments, though those siblings are not named 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?

"Does not publish or schedule" draws a useful boundary against sibling tools like schedule_post and prepare_campaign, and the attribution caveat constrains downstream reasoning. However there is no explicit statement of when to reach for this tool versus alternatives, so usage is only implied.

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