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

With no annotations, the description carries the behavioral burden. It communicates a read-only listing behavior and the content returned, which is sufficient for a zero-parameter list operation; it does not claim side effects or require caveats like pagination.

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 sentences with no fluff: the first defines the listing behavior, the second gives the follow-on workflow. Useful information 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?

For a zero-parameter list tool, the description covers what is returned (templates with task counts and typical durations) and what to do next. It does not spell out the exact return shape, but with no output schema that is a minor gap.

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 tool has zero parameters and the schema fully reflects that, so the baseline 4 applies. There is nothing for the description to add about parameters.

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 uses a specific verb ('List') and a specific resource ('LoopGantt's industry project templates') while adding output details (task counts and typical durations). The workflow reference to get_template and create_gantt immediately distinguishes this discovery action from the sibling creation/fetch tools.

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 clearly places list_templates at the start of a workflow: pick a template, fetch with get_template, adapt, then create_gantt. It does not explicitly state when not to use it or contrast it with schedule_project, so it misses the full 'alternatives' bar, but the intended context is unambiguous.

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