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OpenClip

by app.openclip
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Get Render Status Tool

get_render_status
Read-only

Get the render state of a video's viral moments. Pass the video id (a hashid from list_videos); optionally pass a single viral_moment id to narrow to one moment.

Each entry reports status:

  • completed — a final render exists; rendered_clip is its URL.

  • rendering — a render was dispatched and is in progress (keep polling).

  • failed — the render failed and can be requested again.

  • skipped — rendering was skipped for this moment.

  • not_rendered— no render has been requested for this moment yet.

Render completion is derived from the moment's rendered clip, not any intermediate flag. Poll every 10-15 seconds only while rendering. Stop on completed, failed, skipped, or not_rendered. After 15 minutes, stop polling and report the current state if still rendering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesThe video id (hashid) from list_videos.
viral_momentNoOptional: a single viral moment id to narrow the result.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesThe video id (hashid) these renders belong to.
rendersYesOne entry per plan-visible, auto-processed viral moment.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "renders": {
+      "description": "One entry per plan-visible, auto-processed viral moment.",
+      "items": {
+        "properties": {
+          "rendered_clip": {
+            "description": "URL of the final rendered clip. Null unless `status` is `completed`.",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "status": {
+            "description": "`rendering` means keep polling; `completed` means `rendered_clip` holds the final URL; `failed`, `skipped` and `not_rendered` can all be retried with render_clip.",
+            "enum": [
+              "completed",
+              "rendering",
+              "failed",
+              "skipped",
+              "not_rendered"
+            ],
+            "type": "string"
+          },
+          "viral_moment": {
+            "description": "The viral moment id (hashid). Pass it to render_clip to (re)render this moment.",
+            "type": "string"
+          }
+        },
+        "required": [
+          "viral_moment",
+          "status",
+          "rendered_clip"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "video": {
+      "description": "The video id (hashid) these renders belong to.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "video",
+    "renders"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.3/5.0
Behavior5/5

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

The readOnlyHint annotation already establishes this is a safe read, and the description adds substantial context beyond it: the full meaning of each status value, the fact that completion is derived from the rendered clip rather than an intermediate flag, and the cadence/terminal conditions for polling. This is exactly the behavioral detail an agent needs for a long-running render flow.

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

Conciseness5/5

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

Front-loads the purpose in the first sentence, then uses an efficient indented list for the status enum values and a compact paragraph for polling rules. Every sentence carries actionable information and nothing is repeated across sections.

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?

Despite the output schema existing, the description goes further by enumerating the status values and their implications, which is the part of the response semantics an agent must reason about. With annotations covering safety and the schema covering inputs, nothing needed to call this correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents that `video` comes from list_videos and that `viral_moment` narrows the result. The description restates this without adding format, syntax, or edge-case detail, so the baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource: it retrieves the render state of a video's viral moments, scoped to a video id and optionally a single moment. This is clear enough to separate it from the other status tools (get_video_status, get_tool_job_status, get_ugc_job_status), but it never explicitly contrasts itself against them, so an agent must infer which status tool applies to which resource.

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

Usage Guidelines4/5

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

Gives clear operational context: pass the video hashid from list_videos, optionally narrow to one viral_moment. The polling rules are unusually explicit (poll every 10-15s only while `rendering`, stop on the other states, give up after 15 minutes). It stops short of naming an alternative tool to use instead, which is the only missing piece for a 5.

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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