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Hermoso

by io.github.hermoso-ai

Stitch multi-scene video

stitch_video

Render a multi-scene STITCHED video (≥2 scenes) — ONLY for spots LONGER than ONE clip of the chosen model. A multi-beat ad that FITS one clip renders better and cheaper as ONE single-pass generate_video/render_ad (a single generation carries the whole hook→demo→payoff arc) — never stitch those. What fits is the model’s own maximum from hermoso_capabilities, not a fixed number: 15s on most models, 30s on the longest-clip one, so a 30s spot need not be stitched at all if you name that model. Blocks until done. Spends credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNovideo model id from hermoso_capabilities — omit to let the router pick
voiceNovoiceover voice name, e.g. Rachel / George
scenesYesarray of scene objects (visual + optional voiceover/seconds)
voiceoverNofull voiceover script spoken across the scenes
resolutionNo1080p (default), or 480p/720p for a cheaper draft
aspectRatioNooutput aspect ratio, e.g. 9:16 (default) / 1:1 / 16:9
durationSecondsNototal spot length in seconds (defaults to the sum of the scenes’ seconds)

TDQS

A4.6/5.0
Behavior4/5

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

Annotations only declare it is not read-only and not destructive. The description adds critical behavioral info: 'Blocks until done' and 'Spends credits' - both beyond the annotations. It could also mention what the output resource is (e.g., a video URL), but the key side effects (blocking and cost) are disclosed.

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 compact but dense, with every sentence serving a purpose. It frontloads the purpose, then immediately provides usage conditions, alternatives, and a concrete example of how to determine fit. No filler or repetition.

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 complexity (7 params, one required) and no output schema, the description covers the critical aspects: when to use, how to determine fit, and what to expect (blocking, cost). It could be slightly more explicit about the output (e.g., 'returns a video file path'), but the current description is sufficient for an agent to decide and invoke correctly.

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 baseline is 3. The description enriches parameter understanding by clarifying the 'model' parameter ('video model id from hermoso_capabilities — omit to let the router pick') and explaining the logic behind durationSeconds (defaults to sum of scenes). This goes beyond bare schema descriptions.

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 opens with a specific verb+resource: 'Render a multi-scene STITCHED video (≥2 scenes)'. It immediately distinguishes itself from single-generation tools like generate_video/render_ad by emphasizing the multi-scene stitched nature. This clearly separates it 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?

Explicit guidance is provided: 'ONLY for spots LONGER than ONE clip of the chosen model' and 'never stitch those' that fit one clip. It names the exact alternative (generate_video/render_ad) and references hermoso_capabilities to determine the model's maximum clip length, giving concrete decision criteria.

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

A3.7/5.0
Disambiguation2/5

With 293 tools, the surface is enormous and many tools have overlapping purposes—multiple posting tools (post_to_meta, post_to_linkedin, schedule_post, etc.), multiple analytics tools per channel, and several search tools (search_meta_ads, search_instagram, search_reddit...). While each description is detailed, the volume makes it difficult for an agent to reliably distinguish between similar tools without careful reading, leading to frequent misselection.

Naming Consistency4/5

The naming is largely consistent with a verb_noun pattern (post_to_*, list_*, create_*, delete_*, update_*, manage_*). There are clear families for major operations. A few outliers like 'google_business_account', 'hermoso_capabilities', and 'store_get' break the pattern, but the overwhelming majority follow a predictable structure, making navigation somewhat easier.

Tool Count1/5

293 tools is far beyond any reasonable scope for a single MCP server, even for a comprehensive marketing platform. The calibration guide flags 50+ as an extreme mismatch, and this is nearly six times that threshold. Such a large surface overwhelms context windows, increases the probability of misselection, and makes it impractical for agents to learn or use effectively.

Completeness4/5

The tool set covers a vast domain: ad creation and rendering, posting across nine+ social channels, analytics and reporting, file management (Drive/OneDrive), competitor research, brand management, and more. It appears to provide CRUD and lifecycle coverage for most resources. While there may be minor gaps given the immense scope, the overall coverage is impressively comprehensive.

Resources