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hermoso-ai

Hermoso

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Make template ad

make_template_ad

Render native-style template ads from pure HTML to turn product images and copy into believable social video ads (chat, notes, kinetic type) at scale — no AI model needed.

Instructions

Render a NATIVE-STYLE TEMPLATE ad from pure HTML — no AI video/image model in the loop, renders in ~30 seconds for a couple of credits. Perfect for native-feel social ads at volume. YOU author the content (short, casual, believable — never marketing-speak). Templates (pass as config.template): 'imessage-chat' (VIDEO ~15s: a real-looking iMessage thread where a friend reveals the product as a rich-link card; config: { thread: { contactName, messages: [{from:'them'|'me', text?, product?:{image,title,domain}}] }, theme?:'dark'|'light', endCard:{headline,cta,domain,logo?,color} } — 4-6 short lowercase bubbles, product card mid-thread from 'me', 1-2 excited replies after); 'chatgpt-chat' (VIDEO: a ChatGPT answer streams the punchline; config: { question, answer (may bold the brand), productImage?, endCard }); 'apple-notes' (VIDEO: an iPhone note types itself out; config: { title, lines: string[], theme?, endCard }); 'value-prop' (VIDEO ~17s kinetic typography: config: { hook (≤40 chars), claims: string[] (3-5 COMPLETE phrases, ≤6 words / ≤34 chars each — a finished thought, NEVER a clipped clause like 'Looks good on any'), productImages: string[] (2-3 DISTINCT photos — one rotates per card), palette: string[], endCard }); 'static-mockup' (IMAGE: config: { style:'imessage'|'notes'|'card', size?:{w,h}, ...style fields }); 'airdrop-carousel' (VIDEO ~10s: an iOS AirDrop share card springs up and cycles 3-16 REAL product photos to a full-lineup payoff; config: { brandName, products: [{image, title?}], contactLine?, endCard }); 'app-ui-tour' (VIDEO ~12-16s for APP brands: floating-iPhone mockup walks through REAL app screenshots with kinetic captions; config: { hook?, appName, iconImage?, beats: [{screenImage, caption}] (2-6), palette?, fontStack?, endCard }); 'imessage-cascade' (VIDEO ~12s: iOS notification banners spring in and stack over a blurred backdrop; config: { notifications: [{sender, text}] (4-8), backgroundImage?, endCard }); 'photo-grid' (VIDEO ~8s: collage assembles real photos one at a time; config: { title?, photos: [{image, label?}] (4-9), palette?, fontStack?, endCard }); 'vignette' (VIDEO ~12s: cinematic Ken-Burns hero film; config: { hook, lines: [2-4 ≤40ch], heroImage, palette?, fontStack?, endCard }); 'kinetic-type' (VIDEO ~9-15s typographic motion design with NO VOICEOVER — it is NOT a silent asset: it always carries its own synthesised SFX (whoosh/tick/chime) and, once a curated track is on file, the family's loudest music bed at -16 LUFS; config.music:'off' silences the bed but never the SFX: 3-6 short phrases each land word by word on a full-bleed brand card (product beats caption the phrase over the photo instead), the longest word picked out in the brand accent, and a skewed accent slab wipes every cut; supply productImages and every OTHER beat becomes a full-bleed product shot with its phrase captioned over it — with none it renders as pure typography, so it needs NO photos; config: { phrases: string[] (3-6, ≤34 chars each — punchy, declarative, ONE idea per phrase, a finished thought never a clipped clause), productImages?: string[] (up to 4 DISTINCT photos), palette?: string[], fontStack?, endCard }); 'myth-vs-fact' (VIDEO ~15-26s VO-FIRST kinetic explainer with a real VOICEOVER — the family's ONE paid-audio format: a calm-authority read busts 2-4 myths, each MYTH line slamming in with a red per-line strike then the counter FACT line landing bold+affirmative, word-level KARAOKE lighting each word as the VO speaks it; config: { pairs: [{ myth (≤50ch, the common wrong belief), fact (≤60ch, the corrective truth — wrap its payoff phrase in [brackets] to accent it) }] (2-4), palette?, fontStack?, endCard }. Real product truths only — NEVER invent stats. Costs the flat template credits PLUS a small voiceover charge); 'carousel' (MULTI-IMAGE: 5-10 branded 1080×1080 PNG slides for Meta/LinkedIn/IG carousels — returns an images[] array, one PNG per slide; config: { cover: { hook?, title }, slides: [{ headline (≤8 words), support? (≤16 words), stat?: { value, label } }] (3-8; a stat slide is a REAL user-supplied number like '94%' or '40k+' + a label, never invented), cta: { headline, cta?, domain? }, productImage?, logo?, palette?, fontStack?, endCardColor? }). Every VIDEO format except myth-vs-fact (VO-first, deliberately dry) also gets a mood-matched MUSIC BED when a curated track is on file (the library ships empty — no track means no bed, never a paid generation) under its own SFX, from the curated library — free, no model, no extra credits; set config.music:'off' for a silent cut or a mood name (upbeat/calm/warm/epic/tense/playful/elegant/hype/chill/dramatic) to re-mood it. Image URLs may be any public URL — the server localizes them. Spends a couple of credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configYesthe template config — MUST include config.template (one of the template ids above) plus that template's fields

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.161
    • changedOutput schema / (root)
      Previous value: -{
      -  "$schema": "http://json-schema.org/draft-07/schema#",
      -  "additionalProperties": false,
      -  "properties": {
      -    "jobId": {
      -      "description": "the render job id — poll get_job with this id to resume or inspect",
      -      "type": "string"
      -    },
      -    "model": {
      -      "anyOf": [
      -        {
      -          "type": "string"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "the product-facing label of the model that rendered it"
      -    },
      -    "raw": {
      -      "description": "the raw job result payload (e.g. images[] for carousel template ads)"
      -    },
      -    "stillRendering": {
      -      "description": "true when the render is still in progress — keep polling get_job with jobId",
      -      "type": "boolean"
      -    },
      -    "url": {
      -      "anyOf": [
      -        {
      -          "type": "string"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "the served URL of the finished media (absent/null while still rendering)"
      -    }
      -  },
      -  "type": "object"
      -}New value: +null
  2. Addedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

The description goes far beyond the sparse annotations (readOnlyHint=false, destructiveHint=false): it discloses cost ('Spends a couple of credits'), latency ('~30 seconds'), the music-bed nuance ('library ships empty — no track means no bed, never a paid generation', 'config.music:off silences the bed but never the SFX'), the VO charge for myth-vs-fact, and hard content constraints ('Real product truths only — NEVER invent stats', 'a finished thought, NEVER a clipped clause'). No contradiction with annotations — the non-read-only hint aligns with 'spends credits' and creating an asset.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The content is all necessary, but the structure is a single ~1,500-word run-on paragraph with multiple levels of nested parentheses — e.g., the kinetic-type entry is one ~200-word parenthetical with four nested asides. It is front-loaded with the core purpose, but the lack of line breaks, per-template separation, or bullet structure makes it genuinely hard to parse. This is dense to the point of being unwieldy rather than concise.

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?

Remarkably complete on inputs and behavior: every template's config, constraints, output medium (VIDEO vs IMAGE vs MULTI-IMAGE), duration, and audio treatment are specified. With no output schema, the main gap is the return contract — only 'carousel' explicitly states its return ('returns an images[] array, one PNG per slide'); the video formats imply a rendered asset but never state the response shape or whether this returns synchronously or via a job. Minor, but the cost/latency mention makes the absence noticeable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is nearly empty (a single opaque 'config' object with no properties), so the description carries the entire parameter-documentation burden. It delivers: template IDs, per-template config shapes ('config: { thread: { contactName, messages: [{from:'them'|'me', text?, product?:{image,title,domain}}] }, ... }'), character/quantity limits ('3-5 COMPLETE phrases, ≤6 words / ≤34 chars each'), and enum-like options ('theme?:'dark'|'light''). This is exhaustive added meaning beyond the schema.

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 first sentence states a precise verb+resource+method: 'Render a NATIVE-STYLE TEMPLATE ad from pure HTML — no AI video/image model in the loop'. It differentiates from siblings like generate_video and make_explainer by explicit scope ('template ad' vs generic video generation) and cost/behavior ('~30 seconds for a couple of credits'). The 13 named template variants with per-format purposes make the tool's identity unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear usage context: 'Perfect for native-feel social ads at volume' and per-template guidance ('app-ui-tour for APP brands', 'myth-vs-fact ... the family's ONE paid-audio format', 'carousel for Meta/LinkedIn/IG carousels'). It also sets authoring expectations ('YOU author the content ... never marketing-speak'). However, it never explicitly names sibling tools as alternatives (e.g., when to pick generate_video or make_explainer instead), leaving the contrast implicit in 'no AI video/image model in the loop'.

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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