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Retry video processing

retry_video_processing

Start the HLS encode of a video whose stream_url is null. Starts one unless one has already finished — whether the last attempt failed, died on its way to the encoder, or was never made at all. A workspace that encodes every video on upload needs it only for an encode that failed or stalled. Other workspaces encode on request, and this is the request: reading the asset does not start one. stream_url fills in a few minutes after the call. CALL IT ONCE, NOT IN A LOOP: it cannot tell a running encode from a dead one, so calling it again while one is under way queues a second job. To wait for a result, poll get_asset and watch stream_url. An error back means the encode already succeeded, or the workspace's plan does not stream video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesAsset token of the video
organizationNoWorkspace slug, as returned by list_organizations. Omit it when the account has a single workspace — it is then resolved from your token. Pass it only when the account has several, or when you mean a workspace other than the obvious one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / context
      Removed value: -{
-  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "token",
-  "context"
-]New value: +[
+  "token"
+]
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations mark this non-idempotent and non-read-only, and the description goes well beyond them: it warns that calling in a loop queues a second job, explains that an error response means the encode already succeeded or the plan doesn't stream video, and states stream_url fills in a few minutes later. This is rich behavioral context for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the operation, then constraints, then the loop warning and polling alternative, all in tight prose. Slightly dense with repeated stream_url references, but every sentence carries operational value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, preconditions, idempotency caveat, failure semantics, result-timing, and the polling alternative. With no output schema, the description fully carries the burden for this mutation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, and the description adds the semantic condition tying the token to the video whose stream_url is null and clarifies the effect on stream_url. It does not add detail on the organization parameter beyond the schema, so it lands just above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (start the HLS encode of a video whose stream_url is null), and explicitly carves out the sibling boundary versus get_asset (reading the asset does not start an encode). An agent can distinguish this from get_asset / update_asset without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use (workspaces that encode on upload only need it for failed/stalled encodes; request-and-encode workspaces use it as the request), when-not (assumes you shouldn't loop), and names the alternative for waiting (poll get_asset). This is unusually complete routing guidance.

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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