suggest_evolution

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 clearly states that the tool 'commits nothing' and is a dry-run that validates 'the same way evolve_knowledge does internally.' It also discloses the output (current objects/relations and guidance). While it doesn't mention potential side effects like cost or permissions, the non-mutating nature is explicitly communicated.

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 three sentences long, front-loaded with the core purpose, followed by usage guidance and the alternative preview mode. Every sentence provides essential information without redundancy or fluff. It's concise and well-structured.

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 (two usage modes, dry-run behavior) and the lack of an output schema, the description covers the essential aspects: what it does, when to use it, and that it commits nothing. It names the sibling tool (evolve_knowledge) and the return content. It doesn't detail the exact return structure, but the high-level description is sufficient for an agent to understand the tool's role.

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 coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining the relationship between the two modes: using `description` alone to get guidance, vs. providing an `operations` list for preview. It also clarifies that `operations` accepts the same format as evolve_knowledge, which is not evident from the schema descriptions alone.

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 function: given a session and a change description, it returns current objects/relations and guidance for constructing valid evolution operations. It also distinguishes itself from the sibling evolve_knowledge by positioning it as a pre-check or dry-run, and from validate_knowledge by focusing on evolution operations. The verb 'return' and resource 'guidance' are specific.

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?

Explicit usage guidance is provided: 'Use this before evolve_knowledge to reduce trial-and-error.' It also explains the alternative scenario where you already have a candidate operations list and want to preview its validity. The description clarifies when not to use it (when ready to commit) by contrasting with 'spending a real evolve_knowledge call on a guess.'

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