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Hermoso

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Make template ad

make_template_ad

Render native-style template ads for social media from pure HTML — no AI models, ready in ~30 seconds. Perfect for high-volume, native-feel ad creatives.

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
Install Server

TDQS

A4.6/5.0
Behavior5/5

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

Annotations are all-false, so the description carries the full burden — and it delivers richly. It discloses render time (~30 seconds), cost (a couple of credits), audio behavior (music bed only when a track is on file, never a paid generation; SFX always present unless silenced), output types per template (VIDEO/IMAGE/MULTI-IMAGE with a PNG images[] for carousel), and that image URLs are server-localized. Exceptionally thorough.

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

Conciseness3/5

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

The description is an enormous single paragraph of dense run-on text and deep parentheses that is hard to scan, even though nearly every sentence carries real information. It front-loads the purpose well, but 13 interleaved template specs, character limits, and style guidance would benefit from structured separation. Size is justifiable given complexity, but structure is not.

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?

Complete for a high-complexity tool with no output schema. It enumerates every template variant, its duration, config contract, content constraints (character/word limits, 'never invent stats'), audio behavior, and cost structure. Nothing an agent needs to call it correctly or to pick a template is missing, including the credit implications.

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 schema's single config param is a bare '{}' object with no properties defined, so schema coverage is nominal. The description compensates overwhelmingly — it documents all 13 templates with their full config contracts (e.g., imessage-chat thread/messages/endCard, value-prop hook/claims limits, myth-vs-fact pairs with bracket escape hatch). An agent could construct a correct config purely from this text.

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 NATIVE-STYLE TEMPLATE ad from pure HTML') and immediately distinguishes itself from model-driven tools by stating 'no AI video/image model in the loop'. With siblings like render_ad, make_explainer, and product_sizzle present, this differentiation is essential and well-executed.

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?

Explicitly frames when to use it ('Perfect for native-feel social ads at volume') and imposes clear content authorship rules ('YOU author the content — short, casual, believable — never marketing-speak'). It does not name alternative tools or state explicit when-not-to-use conditions, which the parenthetical about the model-free approach partially covers.

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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