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

Annotations already carry the mutation profile (readOnlyHint=false, destructiveHint=false, idempotentHint=true), so the description needs only to add context. It adds 'existing' and the field focus, which is marginally useful, but it does not disclose partial-update behavior, slug-uniqueness conflict handling, or any workspace-level prerequisites for AI tagging. No contradiction with annotations, but little behavioral depth beyond what is structured.

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 definition is compact — a single useful summary sentence with minimal waste. It is slightly redundant in that the description opens by repeating the title ('Update Tag') before the substantive line, and it front-loads the purpose well. Efficient but with a small redundancy.

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 tool with an output schema and 100% parameter coverage, the description adequately covers the operation's scope and the fields involved. The schema carries parameter details and return shape, so nothing essential is missing for an agent to call it correctly. Fails to earn a 5 only because it could note partial-update semantics or slug-uniqueness implications, though these are minor given the schema's richness.

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 100%, so the schema already documents every parameter (id, name, slug, color, sprite, has_ai_tagging, ai_instructions) in detail, including sprite format rules and length limits. The description's mention of the updatable fields (name, color, slug, AI tagging) offers only a light orientation and adds no syntax or meaning beyond what the schema provides. Baseline 3 is correct.

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 names a specific verb (rename/recolor/adjust) tied to a resource ('existing workspace tag') and lists exactly which aspects are modified: name, color, slug, and AI tagging settings. 'Existing workspace tag' clearly differentiates it from createTag and deleteTag, so an agent can pick it correctly without opening the schema.

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 phrase 'existing workspace tag' implies this is for modifying tags that already exist, contrasting with the create/delete siblings, but the description never explicitly names createTag for new tags or states when not to use this tool. Usage context is implied rather than spelled out, with no explicit exclusion conditions or alternative routing.

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