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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), but the description adds genuinely non-obvious behavior: reads are free and do not count toward the monthly change limit, and an identical read within 30 seconds may return cached data (data_age_seconds). That caching/limit disclosure is real added value beyond the structured fields.

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?

The operation list is front-loaded and earns its space, but the first sentence ('Reads Meta ad accounts') is erroneous dead weight and the repeated 'Meta' reference later ('it does not call Meta') muddles a LinkedIn tool. Otherwise the structure is acceptable.

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 does enumerate the fields each read returns (name, currency, status, objective, spend, impressions, clicks, leads, etc.), which is helpful. However it omits error/empty-result behavior and the multi-account 'connection' nuance (left to the schema), and the Meta/LinkedIn confusion undercuts completeness for a read router that already has many sibling reads.

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 action/tool_name/arguments are already documented, making 3 the baseline. The description adds an example invocation, but the example uses 'list_campaigns' while the schema and the read list use the 'linkedin_' prefix, introducing a naming inconsistency rather than clarity.

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 says 'Reads Meta ad accounts', which names the wrong resource for a LinkedIn tool that has a separate sibling (meta_ads_read) covering Meta. The body recovers by enumerating three clearly-named LinkedIn reads (linkedin_account_summary, linkedin_list_campaigns, linkedin_performance), so the actual purpose is discernible, but the leading mislabel wastes the strongest position and risks mis-routing.

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 explains the two-step router pattern explicitly: 'list_tools' to discover operations, then 'execute' with tool_name/arguments to run one read, including a concrete call example. It also states when the tool is appropriate (read-only, free, outside the monthly change limit). No explicit routing guidance versus google_ads_read/meta_ads_read/microsoft_ads_read siblings, so it stops short of a 5.

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