framesail

Render segment assets

generate_segments

Idempotent

Render every actionable segment asset (images, video clips, overlays) across the project, in dependency order. THE most expensive call in the pipeline: ALWAYS dry_run=true first, show your user the estimate next to get_credit_balance, and wait for a fresh yes before the real run — prior blanket permission ("do the whole thing") does not cover this spend. The staged flow is cheapest: asset_scope="no_clips" first (images + overlays), review, then animate_segment the shots that deserve motion. Pass segment_numbers to render only a subset — e.g. segments 1-18 for the opening minute before committing to the full video. Safe to re-run: completed and currently-generating assets are skipped, so a second call only picks up new/failed work. Async — one job per asset; await_jobs until all complete.

Input Schema

TableJSON Schema

Name	Required	Description
`dry_run`	No	True returns the credit-cost estimate without rendering anything; ALWAYS run true first and get user approval before the real run
`project_id`	Yes	Project ID, as returned by create_project or list_projects
`asset_scope`	No	"" renders everything actionable; "no_clips" is the cheap base pass (images, overlays, fetched b-roll — no generated video clips); "clips_only" renders just the generated clips
`segment_numbers`	No	1-based segment numbers (from get_segments) to render only a subset; omit to render every actionable asset in the project

TDQS

A4.9/5.0

Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: this is the most expensive pipeline call, prior permission does not cover it, re-runs skip completed and currently-generating assets, and execution is async with one job per asset requiring await_jobs. This aligns with idempotentHint=true and gives the agent critical operational guidance.

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 sentence earns its place: purpose, cost warning, staged workflow, subset guidance, idempotency, and async behavior. The most important operational warning is front-loaded immediately after the purpose statement, and there is no 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?

Given the high complexity and no output schema, the description covers the full decision workflow: dry-run before spending, staged scope selection, subset rendering, re-run safety, and async completion via await_jobs. It also references related tools (get_credit_balance, animate_segment, get_segments) that the agent will need to execute correctly. Nothing essential for correct invocation is missing.

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, but the description adds value by showing how parameters work together: using asset_scope="no_clips" as a cheap first pass, and passing segment_numbers like 1-18 to render only the opening minute before committing to the full video. This converts bare parameter options into a coherent invocation strategy.

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: rendering every actionable segment asset (images, video clips, overlays) across the project in dependency order. It clearly differentiates this bulk generation tool from siblings like animate_segment and regenerate_segment_asset by emphasizing project-wide scope and dependency ordering.

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?

The description gives explicit when-to-use instructions: always run with dry_run=true first, show the credit estimate alongside get_credit_balance, and require fresh user approval before the real run. It also prescribes a staged workflow using asset_scope="no_clips" then animate_segment, and explains when to use segment_numbers for subset rendering.

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.

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