List Triggers

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

The description adds value beyond annotations by specifying the return format ('sorted JSON array of trigger name strings') and pagination behavior. Annotations already indicate read-only and idempotent, so no contradiction.

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 well-structured with clear sections (<usecase>, <examples>, <what_it_returns>, <pagination>). It is concise, every sentence adds value, and the main purpose 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?

With zero parameters, comprehensive annotations, and an output schema, the description still covers usage, examples, return format, and pagination. It leaves no gaps for an AI agent to misunderstand.

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 input schema has zero parameters, so the description cannot add parameter meaning. However, it mentions pagination (response cursor), which is contextually relevant. Baseline 4 for zero parameters is appropriate.

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 starts with 'List all triggers in the connected SQLite database,' which clearly identifies the action and resource. It differentiates from sibling tools like listTables and readQuery by specifying 'triggers' and later providing examples that contrast with readQuery.

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 <usecase> section explicitly states when to use the tool, and the <examples> section includes correct and incorrect uses with an alternative (readQuery). This provides clear guidance on when not to use it.

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