call_summary

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the output contents (counts, breakdowns), and importantly discloses the risky default behavior (pagination of 50+ pages of 250 calls) when no window is provided. It does not mention permissions or rate limits, but the key behavioral trait is covered.

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 concise and well-structured: a clear opening statement, a summary of return values, a usage note, and a behavioral warning. Every sentence earns its place, and the key information is front-loaded.

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 complexity and the existence of an output schema (which specifies return structure), the description is largely complete. It covers purpose, usage, and a critical behavioral caveat. The only minor gap is the lack of explanation for account_id and company_id, but these are likely standard filters and the description is adequate overall.

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 0%, so the description must explain parameters. It explicitly explains days and start_date in the note, but does not mention end_date, account_id, or company_id. Those are left to inference. While the critical parameters are covered, the omission of the filter parameters means the description doesn't fully compensate for the schema gap.

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 clearly states the verb ('Summarize') and resource ('calls') and specifies the date-window scope. It distinguishes itself from sibling tools like list_calls by emphasizing aggregate counts instead of individual call data, and the mention of 'weekly/monthly rollups without pulling every call into context' makes the purpose unambiguous.

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 provides clear when-to-use guidance: for rollups and aggregate statistics, contrasted with pulling individual calls. It also gives an explicit usage constraint (requires days>=1 or start_date) and explains the consequence of violating it (pagination of entire history). While it doesn't name a specific alternative tool, the implication is strong enough to guide an agent.

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