render_prompt

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. Description adds important behavioral context: it substitutes variables, returns final messages, and does not call the model. This clarifies the exact operation beyond annotations.

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: first explains what the tool does, second provides usage guidance and distinguishes from a sibling. No unnecessary words, front-loaded with essential info.

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 nested parameters and output schema, the description covers the core purpose, usage context, and comparison to sibling. It notes return of final messages, which suffices given output schema exists. Complete for informed selection.

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%, so baseline is 3. Description does not repeat parameter schemas but implicitly connects the 'variables' parameter to substitution. No extra detail beyond schema, but given full coverage, this is adequate.

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 it renders a prompt by substituting variables and returning final messages without calling the model. It explicitly distinguishes from the sibling tool run_prompt_completion, which invokes the model. The verb and resource are specific.

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?

Explicitly states when to use this tool: 'Use this to verify template output before a completion'. Names the alternative tool run_prompt_completion for when model invocation is needed. Provides clear context that this is for verification only.

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