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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), but the description adds genuinely non-obvious behavior: the figures come from snapshots taken an hour, a day, and a week after publishing, then daily for a month, and nothing is fetched live. That freshness caveat materially affects how an agent interprets and reports results. Return shape and ordering direction (descending?) are left 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?

Three sentences: what it does, how the numbers are produced, and when to reach for it. Front-loaded with the core ranking action and no redundancy against the schema or annotations.

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?

All parameters are optional and fully described in the schema, annotations carry the safety profile, and there is no output schema, so the description needs only to convey what comes back — which it does at a conceptual level (per-network ranked posts by metric) plus the data-freshness caveat. Only the concrete result shape and sort direction are missing.

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 100%, so all five parameters (limit, since, until, sortBy, platform) are already documented in the schema with defaults. The description reinforces the sortBy metric vocabulary and implies per-platform segmentation, but adds no format details, rounding, or tie-breaking rules beyond the schema. Baseline 3 applies.

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 and resource ('ranks published posts') plus the exact ranking dimensions (views, likes, comments, shares, reach, saves, engagement with a formula), which no sibling exposes. It also clarifies the unit of ranking ('each network a post went to is ranked on its own'). It does not name the adjacent tools (list_posts, get_post_analytics), so sibling differentiation is inferred rather than stated.

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?

Gives concrete triggering questions — 'which post worked', 'what did best on LinkedIn this month' — and a forward-looking case (before planning what to write next). That is clear when-to-use context. It stops short of stating when NOT to use it or pointing at alternatives such as get_post_analytics for a single post.

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