Generate coding prompt

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

Annotations already declare readOnlyHint=true, and the description adds that the tool is deterministic and uses no AI spend, reinforcing its safe, read-only nature. No contradictions. Slight gap: does not specify return format or edge cases, but adequate.

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, no filler, front-loaded with purpose and usage. Every word earns its place.

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 low complexity (2 params, simple output), the description covers purpose, usage, and behavioral traits sufficiently. No output schema needed. Complete for its context.

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?

With 100% schema coverage, the schema itself documents both parameters well. The description adds minimal extra meaning (e.g., 'for an annotation' and 'formatted for a target assistant'), aligning with schema but not significantly enhancing it. Baseline 3 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 uses a specific verb ('Render') and resource ('coding prompt for an annotation'), and explicitly distinguishes from a sibling tool ('for a deeper analysis use diagnose_annotation'). Purpose is clear and differentiated.

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 ('A deterministic template (no AI spend)') and when not ('for a deeper analysis use diagnose_annotation'), providing clear context and alternative.

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