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

Annotations already declare readOnly/destructive/openWorld, so the safety profile is covered. The description adds real behavioral context beyond that: the series is bucketed and split by sentiment signal, and the output points are intended as chart input. It does not mention defaults or auth, but the annotation bar is lower here.

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 tightly packed sentences with no filler; the core purpose is front-loaded ahead of the usage/next-step hint.

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?

An output schema exists, so return-value detail is unnecessary, and the description still sketches the shape (bucketed points). For a read-only trend tool with high param coverage, this is nearly complete; only the default granularity and low-quality exclusion behavior are left solely to the schema.

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 80%, so the schema already documents since, until, granularity, and includeLowQuality. The description reinforces the granularity choice (day/week) and the signal split but adds no syntax or format detail beyond the schema, so baseline 3 applies.

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+resource+scope: 'Response volume over time for a project', then qualifies it with the bucketing (day/week) and the signal split. An agent can distinguish this from siblings like project_stats or channel_breakdown without opening a 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?

Explicitly says 'Use for trend / volume-over-time questions' and names the follow-up tool (generate_chart, line). It gives clear triggering context but no explicit when-not guidance or differentiation from adjacent stats tools such as project_stats.

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