evolve_rule

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly states that the daemon 'proposes changes but never inscribes them without consent,' which reveals the non-mutating, advisory nature of the tool. It does not cover permission requirements or failure modes, but the key behavioral trait is disclosed.

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 compact and well-organized: a clear title line, a two-sentence body with a focused purpose statement, and a concise Args block. Every sentence contributes useful information without repetition or filler.

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 output schema exists and there are only two optional parameters, the description provides sufficient context for correct invocation: what the tool does, how to target a specific rule or run batch analysis, and the non-mutation guarantee. It could mention prerequisites like the need for a code index or outcome history, but this is not a significant gap for basic usage.

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 0%, so the Args section is crucial. The description adds meaningful context to both parameters: rule_id is explained as 'Specific rule ID to analyze (omit for batch analysis of all rules)' and project_path as 'Project root'. This goes beyond the schema's bare names and defaults, though project_path could be more detailed about how it is used.

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 'Rule Entropy Analysis -- examine rules for signs of decay and drift' and details how it cross-references rule triggers against the code index and outcome history to produce staleness scores and evolution suggestions. This clearly specifies the verb (examine/analyze), resource (rules), and output, while the phrase 'never inscribes them without consent' distinguishes it from the sibling tool 'inscribe'.

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 makes the intended use clear: analyze rules for decay/drift. It also explains batch vs. specific analysis via the rule_id parameter ('omit for batch analysis of all rules'). However, it does not explicitly name alternative tools or state when another sibling tool should be used instead, so it falls short of full alternative guidance.

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