word_study

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

Annotations already establish the safe read-only, idempotent profile, and the description adds meaningful behavior beyond that: the two lookup paths (direct Strong's entry vs. resolving an English word to the most relevant Greek/Hebrew term), plus the source lexicons used (LSJ, BDB, Abbott-Smith). It does not address ambiguity handling or limits on English-word resolution, so it falls short of a 5.

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 opening sentence, and the resolution mechanics follow before the returns list. The bulleted return inventory is long but each item is substantive rather than filler, so the length is largely earned.

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 no output schema, enumerating the returned fields is exactly the right compensation and it is done thoroughly. The one unaddressed point is that all three parameters are optional, so the description never tells the agent that it must supply either 'word' or 'strongs' to get a useful result.

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 100%, so each parameter is already documented, and the enum on language is explicit. The description adds only a light implication that 'strongs' and 'word' are alternative entry paths, without stating precedence or that all three parameters are optional, so it sits at the schema-driven baseline.

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 first sentence names a specific verb ('look up') and resource ('lexicon entry') and scopes the accepted inputs (Strong's number or Greek/Hebrew/English word). It is clear on its own, but it never distinguishes itself from close siblings such as search_lexicon or search_by_strongs, which is what would push it to a 5.

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 closing sentence gives concrete use cases ('questions about a specific original-language term, a theological term's underlying vocabulary, or the semantic range behind an English rendering'), which is real when-to-use guidance. It stops short of naming when NOT to use it or pointing to the sibling tools that overlap.

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