Skip to main content
Glama

Get an AI video job

get_video
Read-onlyIdempotent

One video job's current state: a SINGLE, IMMEDIATE read that waits for nothing. WHEN: only for one job's raw fields now (cost, refund, why it failed). It is not how you wait (wait_for_generation is) and not how you show a video (the create already opened the card; show_generation brings back an earlier one). Do not poll it. When the user says something failed or looks wrong, read the job and report its actual state and charges instead of arguing from memory. status is queued, processing, succeeded (url is the finished file) or failed (terminal: error.message says why). STORY EPISODES also carry story.stage: frames_review means the run WAITS FOR THE USER (show the frames, do not poll); writing_failed is TERMINAL with status: "failed" (nothing charged, cast saved: offer a fresh generate_story_video with the same cast_member_ids); at ready_to_render the episode url is only the raw stitched preview. After a render, story.render is the LATEST render's verdict: stage: "rendered" with story.render.status: "succeeded" makes story.render.url the FINAL file; failed means that render was refunded and the episode can render again. OUTPUT: tell the user the media URL and one line about it, not raw JSON or job ids.

Input Schema

NameRequiredDescriptionDefault
idYesThe job id returned by `generate_video` or `generate_story_video` (the documented way to read a story episode's stage); `list_videos` carries it too.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent safety, but the description adds substantial context they cannot carry: the call is non-blocking, the full status taxonomy and which states are terminal, that frames_review means waiting on the user, that writing_failed is uncharged and cast-preserving, and the refund semantics of a failed render. This is exactly the behavioral detail an agent needs to interpret results correctly.

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 core constraint ('waits for nothing') and organized with WHEN / OUTPUT markers; every clause carries real meaning. It is dense and fairly long for a one-parameter read tool, but the length is driven by genuinely necessary state semantics rather than filler.

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?

With no output schema, the description takes on the burden of explaining return-value semantics and does so: status values, error.message, story.stage transitions, story.render verdicts, and a closing instruction on how to present results. Nothing material is left unclear.

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?

There is a single required parameter with 100% schema description coverage, and the schema already states which tools produce the id. The description adds no syntax or format detail about `id` itself, only about what the returned status fields mean, so the baseline of 3 applies.

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 ('One video job's current state: a SINGLE, IMMEDIATE read') and explicitly separates itself from wait_for_generation (waiting) and show_generation (displaying). An agent can pick this tool over its many siblings without opening any schema.

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 ('only for one job's raw fields now'), when-not ('Do not poll it', 'not how you wait'), and names both alternatives plus a concrete trigger scenario ('when the user says something failed'). The routing guidance is unambiguous and complete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Directories

Listed in ChatGPT · aicut

Last observed