Skip to main content
Glama

Hermoso

by io.github.hermoso-ai

Make template ad

make_template_ad

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

TDQS

A4.7/5.0
Behavior5/5

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

Annotations provide readOnlyHint=false and destructiveHint=false but no other behavioral detail. The description compensates richly: it discloses cost ('couple of credits'), render speed (~30 seconds), output formats (video, image, multi-image), the absence of AI models, music bed behavior with SFX and how to silence ('config.music:'off''), and even per-template behavior (e.g., myth-vs-fact includes a voiceover charge). No contradiction with annotations exists; it adds substantial value beyond them.

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 extremely long (~800 words) but every sentence carries unique specification for one of 11 templates. It is structured with each template delimited by quotes, config inline, and behavioral notes grouped per template. It could improve by using bullet points or subheadings, but given the breadth and density, the current prose is organized and front-loaded with the core value proposition before diving into template details. It earns a 4 for being appropriately sized relative to complexity.

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?

For a multi-template tool with no output schema, the description is exhaustive: it covers every template's configuration, output type, duration, visual/audio characteristics, costs (including the voiceover add-on for myth-vs-fact), and even content authoring rules (e.g., 'NEVER invent stats'). An agent could invoke any template correctly with zero further information. The absence of an output schema is fully compensated by explicit output descriptions (e.g., 'returns an images[] array, one PNG per slide').

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 has only one 'config' property with empty properties and a generic note. The description is the entire semantic payload: it defines config.template, enumerates each template's exact config keys, value constraints (e.g., '≤40 chars', '3-5 COMPLETE phrases'), and per-template behaviors. With schema coverage at 100% but literally zero property definitions, the description fully compensates and goes far beyond the schema's placeholder.

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 precise verb ('Render') and a specific resource ('a NATIVE-STYLE TEMPLATE ad'), explicitly distinguishing itself from AI video/image model generation. It names 11 distinct templates, each with a clear output type (video, image, multi-image), making the tool's scope unmistakable and separating it from siblings like make_explainer, render_ad, and generate_video.

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?

The description states the tool is 'Perfect for native-feel social ads at volume' and instructs the agent that it 'YOU author the content (short, casual, believable — never marketing-speak)', giving clear usage context. It doesn't explicitly name alternative tools or conditions for when not to use it, but the positioning against AI-heavy generation and the emphasis on template-based rendering makes the intended use clear. A brief contrast with a sibling like make_explainer would elevate it to a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Hermoso toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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