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

With no annotations, the description carries the full burden. It explicitly discloses that answers are AI-generated and advises verifying quotes before publishing, which is critical behavioral information. It also explains each study mode, though it does not discuss response length or other potential limitations beyond the AI-generated warning.

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 purpose, then mode explanations and a verification warning. Every sentence earns its place with no redundancy or filler.

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 moderate-complexity tool with full schema coverage and no output schema, the description is mostly complete. It covers the core behavior, mode semantics, and the critical AI-generated caveat. However, it does not describe the expected response format or length, which would be slightly helpful though not essential.

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 already has 100% parameter coverage with descriptions for passage, mode, and question. The description adds meaningful context by defining what each mode does (e.g., 'summary', 'observe', 'interpret'), going beyond the enum names. It does not need to restate passage/question since the schema covers them.

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 answers questions about Bible passages with Scripture-cited answers, and it lists six specific study modes. This distinguishes it from siblings like get_verse_text (raw text retrieval) and verify_scripture_quote (verification) by emphasizing AI-generated study and Q&A.

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 gives clear usage context ('Ask any question about any Bible verse or passage') and explicitly recommends verify_scripture_quote when publishing, providing an alternative for verification. It does not explicitly exclude siblings like get_verse_text, but the study-vs-text distinction is implied.

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