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

With no annotations, the description must convey behavioral traits. It describes the core behavior but omits details like case-insensitivity of keywords, default matchType, and whether rules are additive or overwrite existing ones. This adequately informs basic use but lacks depth.

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 sentences long, efficient, and front-loaded. It immediately states the action and provides a clear example with no superfluous words.

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 simplicity (3 parameters, no output schema), the description covers the essential functionality and a typical use case. It could mention the default matchType or case-insensitivity, but the schema handles those details, so it is sufficiently complete.

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 100%, so the description does not need to elaborate on parameters. The tool description adds no extra meaning beyond what the schema already provides, meeting the baseline for high coverage.

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's function: adding a keyword auto-reply rule. It explains the trigger condition (inbound message matches keywords) and the action (bot replies with given text), with a concrete example. This distinguishes it from siblings like manage_faq or add_knowledge.

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 notes it is 'good for canned FAQ-style triggers,' providing a clear use case. However, it does not explicitly state when not to use it or mention alternative tools for similar tasks, leaving some ambiguity.

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