neuron_recipe_log

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

With no annotations provided, the description carries the behavioral disclosure burden. It explains the side effect (writing an entry to recipe memory), the kind of data captured, and how the data is later used, which gives the agent a good model of the tool's behavior beyond the name.

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 with no filler. The core action is front-loaded, and each sentence adds useful information: what is logged, what the entry contains, and why it matters.

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 two-parameter logging tool with no output schema, the description covers the essential context: what the tool does, what data goes in, and where to find further structural guidance. It could mention result/return behavior or validation of the slug, but those are minor gaps for this operation.

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 already documents both parameters, and the description adds concrete example fields such as success/failure, sources found, dead ends, and quality score for the free-form entry object. It also points to the Reflect section in agent.md for recipe-specific structure, which is valuable since the entry schema is intentionally open-ended.

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 states a specific verb and resource: log a run outcome to a recipe's memory. It clearly identifies the operation's purpose and distinguishes it from the broader recipe management tools in the sibling list, though it does not explicitly contrast it with the closely named neuron_recipe_memory.

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 implies when to use the tool — after a recipe run, when there is an outcome to record — and notes that the evolve phase consumes these logs. It does not explicitly state when not to use it or how it relates to alternatives such as neuron_recipe_complete or neuron_recipe_memory.

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