speechmatics_list_jobsList transcription jobs (most recent first), with status/data_name/duration. Batch API: GET /jobs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max jobs to return. | |
| created_before | No | RFC3339 date-time; only return jobs created before this time (for pagination). | |
| include_deleted | No | Include deleted jobs in the results. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description adds useful behavioral details: results are most recent first, include status/data_name/duration, and reference the Batch API endpoint. It doesn't cover pagination or rate limits, but the annotation lowers the burden.
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 short sentences deliver the essential information: what is listed, ordering, returned fields, and API endpoint. Every phrase adds value with no redundancy.
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 simple list tool with complete parameter schemas and read-only annotations, the description provides sufficient context (ordering, fields, endpoint). It omits only optional details like default limit or pagination strategy, but these are covered by the schema's parameter descriptions.
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 100% and all three parameters have descriptive text, so the description does not need to explain them. It adds no additional parameter semantics beyond the schema's definitions.
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 uses a specific verb and resource ('List transcription jobs') with ordering and returned fields, clearly distinguishing it from sibling tools like get_job (singular) and delete_job. The scope is unambiguous.
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 states what it does ('List transcription jobs') but does not explicitly compare to alternatives such as get_job for a single job or mention when not to use it. The usage is implied rather than prescribed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action: job management (get, delete, list), transcript retrieval, usage stats, and submission. No overlapping purposes; the only pair that could seem similar (get_job vs get_transcript) is clearly differentiated by descriptions of status vs content.
All tool names follow the exact pattern `speechmatics_<verb>_<object>`, using consistent snake_case. This is highly predictable and makes the API surface easy to navigate.
With 7 tools, the set is well-scoped for a transcription service. Each tool covers a necessary operation without redundancy, and the count feels neither too thin nor overwhelming.
The toolset covers the full lifecycle of transcription jobs: create (transcribe_url), read (list_jobs, get_job), retrieve output (get_transcript), delete (delete_job), plus operational needs (get_job_log, get_usage). No significant gaps for the stated purpose.