Fetch the current status of a transcoding job.
| Name | Required | Description | Default |
|---|---|---|---|
| task_token | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| texts | No | ||
| audios | No | ||
| images | No | ||
| status | No | ||
| videos | No | ||
| percent | No | ||
| duration | No | ||
| warnings | No | ||
| status_url | No | ||
| api_version | No | ||
| source_size | No | ||
| error_description | No |
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?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds no additional behavioral context, such as how status might change over time, whether it's a lightweight check, or any limitations. It simply restates the function without enhancing the agent's understanding.
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 a single, concise sentence with no unnecessary words. It is appropriately brief for a simple status-checking tool, though it lacks the additional context that would make it more valuable.
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?
The tool definition exists within a broader set of related tools, but the description fails to clarify its role relative to siblings like 'get_job_status_detailed' or 'fetch_job_result'. It doesn't mention that a detailed version exists or suggest next steps, making the context incomplete despite the presence of an 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 schema contains one required parameter, task_token, with no description in the schema or the tool description. Schema description coverage is 0%, and the description does not compensate by explaining how to obtain or use the token. The parameter name is self-explanatory but not sufficient for correct invocation.
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 clearly states the tool's function using a specific verb ('Fetch') and resource ('current status of a transcoding job'). However, it doesn't differentiate from the sibling tool 'get_job_status_detailed', so it's not fully distinguished.
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 provides no guidance on when to use this tool versus alternatives like 'get_job_status_detailed' or 'wait_for_job'. There is no mention of prerequisites, exclusions, or recommended scenarios, leaving the agent without selection context.
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.
Most tools are clearly distinct (list_buckets vs list_objects, search vs fetch docs). Minor overlap exists between transcode_video and start_encode2_raw (both submit jobs) and between get_job_status and get_job_status_detailed, but the descriptions explicitly state when to use which, making misselection unlikely.
Names overwhelmingly follow verb_noun (create_bucket, list_buckets, get_download_url, transcode_video). A few deviations like start_encode2_raw, wait_for_job, and download_url_to_bucket break the pure pattern, but the convention is still easily predictable.
13 tools is well-scoped for a video encoding platform: bucket management, transcoding submission/status/wait, result retrieval, and docs search/read. Each tool serves a clear purpose without redundancy or bloat.
The set covers the main lifecycle: create bucket, ingest via copy, transcode (two entry points), poll status, fetch result, and generate download URLs. Missing cancel/delete operations for jobs and buckets are notable but not critical for core workflows, and the docs tools help fill knowledge gaps.
