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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to repeat those. Instead, it discloses critical limitations: it does not know if the user already replied, 'replied' is a floor (only sentiment-scored replies), withdrawn/unreachable invites leave no trace, sentiment is judged once per lead, and leadIds are capped at 200. These caveats go far beyond the annotations and prevent the agent from overstating what the tool knows.

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 description is long but every sentence earns its place. It is front-loaded with the purpose, then usage guidance, then an explicit alternative, then honest limits. The structure is logical and the content is dense without redundancy. It reads as a well-crafted, informative definition rather than a padded one.

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?

Given the tool's moderate complexity, the presence of an output schema (so return format need not be described), and the detailed annotations, the description is complete. It covers what the tool does, when to use it, how it differs from similar tools, and its limitations. No critical information for correct invocation is 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?

The schema covers the sole parameter campaignId with a description ('Campaign to inspect, from list_campaigns or fetch_leads') and 100% coverage. The tool description does not add any additional meaning about the parameter itself; it focuses on output semantics and usage. Since schema coverage is full, a baseline of 3 is appropriate, and the description adds no further parameter-level context.

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 description opens with a precise statement of what the tool returns: a ranked to-do list of what a campaign still needs from a human, enumerating concrete buckets (replied, accepted-but-unmessaged, drafts, uncontacted leads, missing setup). It clearly names the verb (list) and resource (next steps) and distinguishes it from siblings like list_replies and get_campaign_stats. The purpose is unambiguous and actionable.

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?

The description gives explicit trigger conditions: 'CALL THIS WHENEVER THE USER ASKS FOR RECOMMENDATIONS, ADVICE, NEXT STEPS, OR WHAT TO DO.' It also states when to pair it with get_campaign_stats, when to prefer list_replies instead, and advises using it before suggesting new searches. This is exemplary usage guidance with clear alternatives and a rationale.

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