changes_many

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'batch changes' but does not clarify if the tool is read-only or mutates state, what permissions are needed, or if it returns only change times or full data. This is insufficient for a tool that may modify data.

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 two concise sentences with no wasted words. It front-loads the core purpose and adds a usage hint, achieving maximum efficiency.

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 batch operation on multiple signals with 17 siblings, the description lacks details on result structure, pagination, or ordering. However, an output schema exists (though not provided), so return values are assumed covered. The description is minimally adequate but leaves room for ambiguity.

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 all 4 parameters with descriptions, so baseline is 3. The description adds no extra meaning beyond what the schema already provides (e.g., no elaboration on how 'signals', 'start', 'end', or 'limit_per_signal' are used).

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 it does batch changes for multiple signals in a time window, and mentions preferring it for waveform debug context. The name 'changes_many' and sibling 'changes' reinforce that this is the batch counterpart, providing clear differentiation.

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 a weak preference for waveform debug context but does not explicitly state when to use this versus alternatives like the single-signal 'changes' tool. No exclusions or when-not-to-use guidance are provided.

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