List voicemail drops
voicemail_drops_listList voicemail drops: name, has_audio (only drops with audio can be dropped), duration_ms, source, script_text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
voicemail_drops_listList voicemail drops: name, has_audio (only drops with audio can be dropped), duration_ms, source, script_text.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by naming the returned fields and disclosing the business rule that has_audio gates drop eligibility — a behavioral constraint an agent would not otherwise know.
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?
A single sentence with zero filler: verb, resource, then the field list with the one qualifying rule inline. Nothing is front-loaded in the wrong place, and no sentence could be removed without losing 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?
For a parameterless read tool with full annotation coverage, the description supplies the one thing structured data lacks: the shape of the response (name, has_audio, duration_ms, source, script_text). It does not say whether results are paginated, sorted, or capped, which is the only real gap for a list tool with no output schema.
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 tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. The enumerated fields describe the response shape rather than inputs, which is extra value but not parameter semantics.
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 verb+resource ('List voicemail drops') and enumerates the fields returned, so an agent knows exactly what it retrieves. The 'list' prefix and the sibling names voicemail_drops_manage / voicemail_drops_drop make the read-vs-mutate distinction inferable, but the description never explicitly contrasts itself with those siblings.
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?
Usage is only implied by the 'List' verb; there is no explicit statement of when to use this versus voicemail_drops_manage. The parenthetical 'only drops with audio can be dropped' is genuinely useful cross-tool guidance pointing toward voicemail_drops_drop eligibility, but it is framed as a field note rather than routing instruction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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