cantrip_next_prompt

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it generates prompts (implying a read/creation operation), specifies zero credit cost (important for cost management), and mentions the 'project' parameter's override functionality. However, it lacks details on potential errors, rate limits, or authentication needs, leaving some behavioral aspects unclear.

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 highly concise and well-structured in two sentences. The first sentence states the core purpose and key features (context-rich, ontology-baked, zero cost), while the second provides specific usage guidance for the 'project' parameter. Every word earns its place with no redundancy or fluff.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is mostly complete. It covers the purpose, key behavioral traits (zero cost, override functionality), and usage context. However, without an output schema, it does not describe the return value (e.g., prompt format or structure), which is a minor gap for a tool that generates outputs.

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 description coverage is 100%, so the schema already fully documents both parameters. The description adds minimal value beyond the schema by briefly explaining the 'project' parameter's purpose (to override '.cantrip.json' in specific environments), but does not provide additional syntax, format, or usage details for either parameter. This meets the baseline for high schema coverage.

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's purpose with a specific verb ('Generate') and resource ('context-rich LLM prompt for an opportunity'), and distinguishes it from siblings by specifying it returns a ready-to-use prompt with ontology context baked in. It explicitly mentions zero credit cost, which further differentiates it from potential cost-incurring 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 provides clear context for when to use the tool (to generate prompts for opportunities) and includes a specific usage note about the 'project' parameter overriding '.cantrip.json' in cloud-hosted or multi-project contexts. However, it does not explicitly state when NOT to use this tool or name alternatives among the sibling tools, which prevents a perfect score.

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