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hermoso-ai

Hermoso

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Post-production edit

post_edit

Mechanically edit a rendered video: trim, adjust speed, mute, audio gain, fade out, add watermark, end card, or film grain using ffmpeg, without AI, returning a new video.

Instructions

MECHANICAL post-production on an EXISTING rendered video (its served mp4 URL) — an ordered plan of whitelisted primitives executed by ffmpeg (+ Chrome for typeset cards) in seconds for ~2 credits flat, NO AI model, the original untouched (returns a NEW video). The lane for: append a branded end card ('add an end card with our logo and website' — ADDS its seconds, never re-renders), trim, speed (0.5-2x), mute (whole or a window), audio_gain (-20..+6 dB), fade_out, corner logo watermark, anti-AI film grain. Up to 6 ops per plan, applied in order. Brand assets (name/domain/logo/accent) load from the workspace brand automatically; override per-call if needed. NEVER use generate_video/render_ad for these mechanical asks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opsYesthe ordered edit plan (max 6 ops)
accentNooverride the brand accent hex
domainNooverride the brand website
videoUrlYesthe served URL of the video to edit
brandNameNooverride the workspace brand name

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNothe raw job result payload (e.g. images[] for carousel template ads)
urlNothe served URL of the finished media (absent/null while still rendering)
jobIdNothe render job id — poll get_job with this id to resume or inspect
modelNothe product-facing label of the model that rendered it
stillRenderingNotrue when the render is still in progress — keep polling get_job with jobId
Behavior5/5

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

The description discloses key behavioral traits: returns a new video, original untouched, costs ~2 credits, no AI model, max 6 ops applied in order, and brand assets auto-load. Annotations are minimal; the description adds valuable context without contradiction.

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?

The description is well-structured: opens with purpose and key constraint, lists operations, then usage notes and alternatives. While slightly dense, it is efficient and front-loaded with critical information.

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

Completeness4/5

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

Given the tool's complexity and full schema coverage, the description covers key aspects: input, operations, constraints, cost, and alternative tools. An output schema exists, so return value details are not required. No major gaps.

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%, but the description adds semantics beyond parameter names: e.g., explains that brand assets auto-load, max 6 ops, operations like append_card add seconds without re-render, and override parameters. Enhances understanding significantly.

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 clearly states the tool performs mechanical post-production on an existing video, listing specific operations (trim, speed, etc.) and explicitly distinguishes from sibling tools like 'generate_video' and 'render_ad', stating 'NEVER use generate_video/render_ad for these mechanical asks.'

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 specifies when to use the tool (for mechanical edits on an existing video) and when not (no AI model, no rendering), and explicitly names alternatives. It also explains brand assets load automatically and can be overridden, providing clear context.

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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