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

Annotations already declare readOnlyHint=true, so the trailing 'Read-only' adds nothing, but the description goes well beyond them: days before tracking began are omitted and the start date is returned, each series ends with net change, and omitting `account` yields one series per channel. That is real output-shape behavior an agent can't get from the annotations. It stops short of covering rate limits or volume, keeping it at 4.

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 actual data shape, then the disambiguating example questions, then exclusions — a sensible order. Slightly padded by the redundant 'The same numbers as the Analytics page's follower growth chart' and 'Read-only' sentences, which restate rather than add.

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?

No output schema exists, and the description fully compensates: row granularity, fields, multi-channel series behavior, net-change terminator, and the omitted-days caveat with a start date. An agent has everything needed to call it and interpret the result.

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%, so baseline would be 3, but the description adds meaning the schema doesn't spell out — notably that omitting `account` across multiple channels produces one series per channel, and that pre-tracking days are dropped rather than zero-filled. The period vs. start_date precedence is covered by the schema, so no extra credit there.

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 ('Daily follower counts'), the exact row shape ('one row per day (date, followers)'), and the platform scope ('LinkedIn only'). It also distinguishes itself from get_analytics_summary for non-LinkedIn platforms, so an agent can route without opening either schema.

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 use-case phrasings in quotes ('how have my followers grown day by day?', 'follower count each day in March') and names the alternative with its selecting condition ('for other platforms use get_analytics_summary'). It also points to start_date/end_date for windows the presets don't cover, so scope decisions are explicit rather than inferred.

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