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

Annotations already mark readOnly and idempotent, and the description adds rich behavior: no truncation or regeneration, explicit safety-limit failure, 200-candidate cap, only public finished sermons returned, sources_truncated semantics, hallucination risk, and untrusted-data warning. No contradiction with annotations.

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?

Front-loaded with the core action, then organized into limits, caveats, and verification steps. Though long, every sentence carries selection-relevant or safety-critical information with no 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?

With one parameter and an output schema present, the description covers return behavior, failure modes, source_sermons semantics, verification workflow, and labeling requirements. An agent has everything needed to invoke it correctly and interpret results.

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 single parameter study_id is already fully documented in the input schema, including its origin in search_msza_ai and canonical URL form. The description reinforces that context but adds no new parameter-level detail beyond the schema, so the high-coverage baseline of 3 applies.

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?

States a specific verb and resource: read one saved public AI study by study_id from search_msza_ai. It clearly distinguishes itself from search_msza_ai and from transcript/sermon retrieval tools.

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 limits use to preliminary topic orientation, warns against using it as factual evidence, and directs verification against get_transcript or get_sermon via source_sermons. It also names the preferred alternative when citing evidence.

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