onto_align

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

With no annotations, the description carries full burden. It mentions auto-applying high-confidence matches and dry_run, but does not disclose permanence of changes, reversibility, authorization needs, or whether the tool is destructive. The write operation (inserting triples) is only implied via dry_run parameter.

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 two sentences, front-loaded with the main purpose, and avoids redundancy. It is efficient but could be slightly more structured (e.g., separating detection from auto-application). Minor improvement possible.

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?

Despite the tool's complexity and no output schema or annotations, the description omits return value details, side effects (permanent ontology modification), and guidance on interpreting dry_run results. Missing critical context for effective use.

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%, with each parameter already described. The description adds context about how min_confidence is used for auto-apply and the purpose of dry_run, but does not significantly extend beyond schema descriptions. Baseline 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 clearly states the tool detects alignment candidates using specific ontology relations (owl:equivalentClass, skos:exactMatch, rdfs:subClassOf) and multiple methods (label similarity, property overlap, etc.), distinguishing it from siblings like onto_map or onto_similarity.

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 this tool is for automatic alignment detection and application, but does not explicitly state when to use it versus alternatives like onto_map (manual mapping) or onto_similarity (similarity computation). No when-not-to-use or alternative recommendations are provided.

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