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

Description adds behavioral context beyond annotations: it mentions personalization based on background and instructs to ask user first. Annotations already indicate readOnly and idempotent, which the description is consistent with. No contradictions.

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?

Description is very concise (3 sentences) yet covers purpose, usage, exclusions, and user instruction. No wasted words; front-loaded with main purpose.

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 simple tool with one parameter and no output schema, the description provides complete context: what it does, when to use, what not to use, how to interact (ask background). No missing information.

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?

Input schema covers the single parameter completely with enum values and description. The description reiterates the instruction to ask background but adds minimal new meaning. Baseline 3 is appropriate as schema coverage is 100%.

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?

Description clearly states the tool generates a personalized Canton Network onboarding path, using specific verb 'generate' and resource. It distinguishes from siblings like search, get_faq, and get_api_reference by scoping to Canton-only and specifying usage contexts.

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?

Explicitly provides usage conditions: 'Use when a developer asks how to start building... Do not use for onboarding to other chains... Prefer this over 'search'... use get_faq for a single specific gotcha and get_api_reference for API details.' Also instructs to ask user's background first.

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