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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds genuinely new behavior: an exceptional safety limit fails loudly instead of returning partial text, source_sermons draws from at most 200 linked candidates, sources_truncated refers to the candidate cap and not text truncation, and the response flags AI-generated origin with provenance fields. That is material context an agent could not get from the structured fields.

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?

Purpose is front-loaded in the first sentence and each subsequent sentence carries a distinct disambiguation (fail-explicit behavior, candidate cap vs. truncation, provenance). It is dense and slightly prose-heavy, but no sentence is 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?

An output schema exists, yet the description still clarifies the two most confusable return fields (source_sermons and sources_truncated) and the provenance marker, so an agent knows what a successful response means. Nothing needed to invoke the tool correctly is missing.

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?

There is a single parameter and schema description coverage is 100%, with the schema already explaining that study_id is an exact sourceId from search_msza_ai or a canonical msza.ai URL. The description's 'by study_id' adds no format or syntactic detail beyond that, so the baseline 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?

The description gives a specific verb+resource with scope: 'Returns one saved public AI study by study_id with its complete public text and source-sermon metadata.' This clearly separates it from list/search tools and from get_sermon by naming the AI-study resource. It stops short of naming a specific sibling to route away from, so it lands just below the top tier.

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 body offers no when-to-use or when-not-to-use guidance and never names an alternative such as search_msza_ai or get_sermon. The only hint that this is a follow-up to a search lives in the schema's study_id description, not in the tool description itself.

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