dictionary

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds real value by disclosing the fallback-to-full-text behaviour when no headword matches, but says nothing about result ordering, which lexicons win when several match, or output truncation.

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?

Two sentences, front-loaded with the action and corpus, then the fallback. The module enumeration is dense but earns its place by telling the agent what content exists. 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 no output schema and no parameter descriptions, the description is the only prose an agent gets. It covers scope and fallback adequately but omits result shape, truncation via max_chars, and how module selection interacts with the search fallback.

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 coverage is 0%, so the description must carry the parameter burden. It implicitly maps 'term' to a headword or Strong's number and names the dictionary modules that the `modules` filter presumably selects from, but `max_chars` (default 4000) is never mentioned, so truncation behaviour is invisible.

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 + resource ('look up a headword or Strong's number in the dictionaries and lexicons') and enumerates the source collections, so the agent knows exactly what corpus is queried. It does not explicitly contrast with near-neighbours like dictionary_modules or search, so it falls short of 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 trigger condition is implied — use it when you have a headword or Strong's number — and the fallback to full-text search is disclosed. However, there is no explicit when-not or pointer to the sibling that lists modules or to `search` for free-text queries, leaving the routing partly to inference.

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