Update dictionary words

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

The description adds meaningful behavior beyond the annotations: words are trimmed and de-duplicated, case is significant, and the tool returns both the sent payload and the resulting dictionary. These details help the agent predict side effects and interpret the response, especially since no output schema is present.

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 three sentences with no filler. It front-loads the primary action, then adds essential processing semantics, and finally describes the return value in a natural order. Every sentence contributes useful information.

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?

Given a simple two-optional-parameter tool, no output schema, and annotations covering read-only, destructiveness, and idempotency, the description provides what an agent needs: purpose, parameter behavior, processing rules, and return shape. It is complete for correct invocation in this context.

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 schema provides no descriptions and names only 'add' and 'remove', so the description must compensate. It does so by explaining the intended function of both arrays and by adding important value semantics like trimming, de-duplication, and case sensitivity. It could go further, for example by describing behavior when the same word appears in both arrays, but for simple string arrays the current coverage is strong.

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 opens with a specific action ('Add or remove words') and names the exact resource ('the custom dictionary of the local OpenWhispr app'). This clearly distinguishes it from sibling tools, especially list_dictionary, and leaves no ambiguity about what the tool does.

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 makes its core use case clear: modify the custom dictionary by adding or removing words. However, it does not explicitly state when to prefer this tool over alternatives, nor does it mention read-only alternatives like list_dictionary for inspection-only use. The usage context is implied rather than explicitly guided.

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