neuron_recipe_get

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

No annotations are provided, so the description carries the full burden. It implicitly conveys read-only behavior via 'Get' and 'before running it', and it lists what the call returns. However, it does not explicitly mention lack of side effects, error behavior, or auth requirements, leaving minor gaps.

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 exactly two sentences with no filler. The primary action and key contents are front-loaded, and the usage sentence earns its place by adding practical context.

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 simple tool with one required parameter and no output schema, the description is largely complete: it explains what is returned and when to use it. It omits response format and error details, but those are less critical at this complexity level.

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 input schema already provides 100% coverage for the single 'slug' parameter, including an example. The description adds no additional parameter-level meaning, so the baseline score of 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 opens with 'Get a recipe's full contents', clearly stating the action and resource. It enumerates the specific components returned (agent.md, recipe.yaml, accumulated learnings, variable definitions), which distinguishes it from siblings like neuron_recipe_run and neuron_recipe_list.

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 second sentence gives an explicit use case: 'Use this to understand what a recipe does before running it.' This is a clear context for when to use the tool, but it does not name alternative tools or state explicit when-not-to-use conditions, so it doesn't reach the 5-level of guidance.

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