corpus_create

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

Annotations already indicate mutation (readOnlyHint=false), idempotency (idempotentHint=true), and non-destructiveness (destructiveHint=false). The description adds the valuable note that 'Each corpus uses a fixed embedding model', but doesn't disclose other behavioral traits like side effects or confirmation behavior.

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 a single, front-loaded sentence with no redundant words. It efficiently communicates the tool's core purpose and one key constraint (fixed embedding model).

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 creation tool with two well-documented parameters and no output schema, the description is adequate. It conveys the essential context (creation, use case, embedding model constraint). It could mention what happens on duplicate corpus_id, but the idempotentHint partially covers that.

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?

The input schema provides 100% coverage of parameters, including descriptions for corpus_id and label. The description's phrase 'named corpus' implicitly aligns with corpus_id, but adds no additional semantic detail beyond the schema.

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 uses the specific verb 'Create' with the resource 'corpus' and clearly states its purpose: 'for semantic search over transcripts'. This distinguishes it from sibling tools like corpus_add, corpus_search, corpus_list, and corpus_delete.

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 provides clear context: it's for creating a named corpus for semantic search over transcripts. While it doesn't explicitly mention alternatives or exclusions, the context makes it apparent when to use this tool versus corpus_add or corpus_search.

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