get_prompt_template

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

No annotations are provided, so the description must fully convey behavioral traits. It describes the return value but does not disclose whether the operation is read-only, requires permissions, or has other side effects. The tool likely reads a template, but this is implicit.

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 concise, using a brief role statement followed by structured Args/Returns sections. Every sentence is meaningful, and there is no extraneous text. It could be slightly more compact, but it is well-organized.

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?

The description covers the purpose and parameters adequately given the tool's simplicity (two optional params) and the presence of an output schema. However, it lacks usage guidance and behavioral context that would be helpful for an agent, especially with no annotations.

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 has no property descriptions (0% coverage), so the description must fill the gap. It explains that 'section' gets a specific part and 'mode' controls verbosity, adding meaning beyond the raw schema. However, it does not list valid section names or mode options, leaving some ambiguity.

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 provides a 'comprehensive prompt template for LLM interactions with Airflow operations,' which is a specific verb-resource combination. This distinguishes it from siblings that focus on DAG data, configs, or state changes.

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?

No guidance is given on when to use this tool versus alternatives like the many sibling tools. The description does not mention any exclusions or context that would help an agent decide when to invoke it over other tools.

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