neuron_rules_get

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

With no annotations provided, the description carries the transparency burden and does meaningful work: it discloses the file source, explains the priority semantics (rules override recipe strategies), and enumerates the three levels with a concrete 'never' example. It does not describe the return format or behavior when the file is absent, but for a read-only config access tool the disclosed semantics are strong.

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?

Three sentences with no filler; the core action and file path are front-loaded in the first clause. Every sentence adds distinct value: target resource, constraint semantics, level definitions, and pointer to the sibling tool for task-specific rules.

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 zero-parameter read-only tool with no output schema, the description covers the essential context: file location, rule priority, level meanings, and where task-specific rules live. The only notable gap is the lack of detail about the returned structure or empty-file behavior, but that is minor for a simple reader.

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 tool has zero parameters, so there is no schema burden for the description to carry. The baseline for a parameterless tool is 4, and the description appropriately avoids inventing parameter-like detail; it even clarifies that task-specific rules are not parameters here but are passed via neuron_recipe_run.

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 the specific verb-resource pair 'Read the active rules' and pinpoints the exact file path (~/.neuron/rules.yaml). It distinguishes the tool from its main sibling by explaining that task-specific rules belong to neuron_recipe_run, and the contrast with neuron_rules_set is implicit in the 'Read' verb.

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 gives clear context for when this tool is relevant: reading hard constraints that override recipe strategies. It also explicitly directs task-specific rules to neuron_recipe_run, which is a concrete when-not-to-use pointer and names the alternative tool.

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