framesail

Animate segment

animate_segment

Animate one segment in a single call: flip it to a generated video shot (keeping its rendered image as the clip's first frame) and START the clip render immediately. BILLS video credits on this call — the segment's image must already be rendered (400 otherwise). A refused generation (out of credits, already running) rolls the flip back, so the segment is either animating or exactly as it was. This is the ONLY way to a generated video (voice=true for a Talking Head) — change_segment_type refuses that target; it owns the other kind switches (real media, overlay scene, back to a still — segment_type "image" with carry_frame=true reverts an animated shot for free). Async — returns {ai_job_id, segment}; await_jobs until the clip completes.

Input Schema

TableJSON Schema

Name	Required	Description
`voice`	No	True lip-syncs the on-frame speaker to the voiceover (lip-sync model family — bills the exact segment length, so long segments cost proportionally more); False is an ordinary prompt-driven clip. Always explicit, never inferred.
`project_id`	Yes	Project ID, as returned by create_project or list_projects
`segment_number`	Yes	1-based segment number, as reported by get_segments

TDQS

A4.9/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly: it discloses billing of video credits, a 400 error when the image is not rendered, rollback behavior on refused generation, and the async contract returning {ai_job_id, segment}. This is far beyond a minimal safe-read/write statement.

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?

The description is dense but every clause earns its place: core action, sequence semantics, billing, error precondition, rollback, sibling differentiation, and async completion. The structure front-loads the main action and immediately gives the agent the highest-stakes facts.

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?

Even without an output schema, the description states the return shape and follow-up call, making it complete for invocation. It covers prerequisites, failure modes, cost implications, and alternatives, leaving no obvious gap an agent needs before calling the 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; the description adds value by tying voice=true to the Talking Head use case and clarifying that the voice flag is 'always explicit, never inferred.' It does not add much for project_id or segment_number, but the schema already documents them well.

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?

The description states a specific verb and resource: 'Animate one segment in a single call: flip it to a generated video shot... and START the clip render immediately.' It clearly distinguishes itself from change_segment_type, which 'owns the other kind switches,' so an agent can tell this tool from siblings.

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?

It explicitly frames this call as 'the ONLY way to a generated video' and names the alternative for other segment-type switches: change_segment_type. It also gives the prerequisite (image must already be rendered), the async follow-up (await_jobs), and notes that voice=true is for a Talking Head.

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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TDQS

A3.6/5.0

Disambiguation3/5

Several tool families overlap in purpose, such as await_jobs/get_workflow_status/get_pipeline_progress, update_segment_content/update_segment_prompts, director_note/project_director_note, and scan_script/rescan_voice_blocks. The descriptions do a good job distinguishing them, but an agent must read carefully to avoid misselection, and there are more than a couple of confusable pairs.

Naming Consistency4/5

The set overwhelmingly follows a verb_noun snake_case convention with clear prefixes like get_, list_, set_, update_, create_, and delete_. Minor exceptions such as director_note, project_director_note, browse_audio_library, and whoami keep it from being perfectly consistent.

Tool Count1/5

At 72 tools, this is far beyond the 50+ extreme range and creates a heavy navigation burden for an agent. Even though the pipeline is complex, this many tools is not well-scoped for an MCP surface.

Completeness4/5

The surface covers the full script-to-export pipeline: styles, assets, voices, storyboards, segments, scenes, and rendering all have substantial lifecycle support. Some gaps exist—no delete_channel, delete_segment, delete_voice_block, or delete_provider_key—but most missing operations can be worked around through existing tools.

Resources

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