quick_add

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

Annotations are all false/default (readOnlyHint false confirms this writes, which aligns). The description discloses the NLP-parsing behavior, which is the key behavioral trait. However, it doesn't mention potential side effects like how the event is committed, whether it's immediate, or what happens to the natural-language string if parsing fails. With no annotations carrying behavioral context, the description carries more burden but provides only modest disclosure.

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?

A single, focused sentence that immediately states the verb (create), the resource (event), and the key mechanism (natural language via NLP parser). Zero waste, perfectly front-loaded with the most important differentiator.

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 tool with 100% schema coverage, an output schema, and clear annotations, this is reasonably complete. The NLP-parsing behavior is stated. Could benefit from a note about parsing-failure behavior or what structured fields the parser produces, but given the output schema exists and the tool is conceptually simple, this is adequate.

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 coverage is 100%, both parameters (text, calendar_id) are fully described in the schema. The description adds the NLP-parsing context which explains how 'text' is interpreted, but doesn't add meaning beyond what the schema provides for calendar_id. Baseline 3 is appropriate since 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?

The description clearly states the tool creates events from natural language strings using an NLP parser, which distinguishes it from the sibling 'create_event' (which likely takes structured fields). It identifies the key differentiator (NLP parsing) that separates it from sibling tools. However, it doesn't explicitly name the sibling alternative, so it could be slightly stronger.

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 implies this is for natural-language input and distinguishes it from structured event creation. It doesn't explicit state 'use create_event for structured input' but the NLP mention strongly signals when this tool is appropriate. The distinction from create_event is clear contextually but not explicitly stated as a when-not rule.

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