get_prerequisites

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

No annotations provided, so description carries full burden. It discloses matching behavior (case-insensitive, partial name resolution), output format with examples, and edge cases (root concept, not found). Lacks mention of side effects or rate limits, but these are not critical for a read operation.

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?

Well-structured with Args and Returns sections, and front-loaded with purpose. Somewhat verbose but every sentence adds value, so it maintains clarity without being overly long.

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 simplicity (2 parameters) and lack of output schema, the description is remarkably complete. It explains purpose, usage context, parameter behavior, return format with examples, and edge cases. No significant gaps.

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 description adds significant meaning. For 'domain' it specifies to use exact name from list_domains; for 'concept' it details matching behavior and partial resolution. This compensates well for the lack of schema descriptions.

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 purpose: 'Return the full ordered chain of concepts to understand before a target concept.' It specifies the verb, resource, and scope, and distinguishes from siblings by directing to alternative tools for different tasks.

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 states when to use: 'for onboarding, gap-filling, or sequencing study.' Also provides clear exclusions: for two-directional neighborhood use query_ckg, for exact name resolution use search_concepts. This provides excellent guidance.

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