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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, so the safety profile is covered. The description adds real context beyond that: each row is a single LinkedIn call with its status, and results are paginated via limit/offset. It does not state defaults or caps for limit, which would be the remaining useful detail.

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?

Two sentences, no filler, and the core action is front-loaded ahead of the alternative-tool pointer. Every clause earns its place.

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?

For a read-only, idempotent log-retrieval tool with full parameter coverage, an output schema, and declared annotations, the description supplies everything an agent needs: purpose, filter, pagination, and the totals alternative.

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 the schema already documents account_id, request_type, limit, and offset with examples. The description only restates the same filter/pagination concepts already present in the schema, adding no syntax or default values. Baseline 3 applies when the schema does the heavy lifting.

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 (get request logs for a LinkedIn account) plus the scope modifiers it supports. It explicitly distinguishes itself from the sibling get_account_request_logs_stats, which handles totals, so an agent can choose between them 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 a concrete use case (debugging a failing account, seeing each LinkedIn call with its status) and names the alternative tool for totals. The routing condition between this tool and get_account_request_logs_stats is explicit.

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