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Hermoso

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by hermoso-ai
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JavaScript
Remote

Generate text

generate_text

Generate ad copy, hooks, scripts, rewrites, or brainstorms with AI writing models. Answers as a marketing copywriter by default; use raw mode for plain responses.

Instructions

Text generation against the writing-model catalog (Claude, Gemini, GPT, Llama, DeepSeek…) — ad copy, hooks, scripts, rewrites, brainstorms. Prompt-only, no ad assembly (for a finished on-brand creative use plan_ad -> render_ad). BY DEFAULT the model answers as a marketing copywriter (a short house system prompt is applied, which is what you want for ad copy); pass raw:true for a plain, unstyled answer from the model itself with NO system prompt at all. model = a writing-model id from hermoso_capabilities (omit for the default Claude orchestrator). Paid (a credit or two by length).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoRAW MODEL ACCESS: send the prompt with NO Hermoso system prompt — the model answers as itself rather than as an ad copywriter. Use it whenever the ask is not marketing copy (analysis, code, extraction, a plain question). Default false: the copywriter framing is applied.
modelNoa writing-model id from hermoso_capabilities (a Claude / Gemini / GPT / Llama / DeepSeek id) — omit for the default
promptYesthe writing task / question

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.161
    • addedInput schema / properties / raw
      Added value: +{
+  "description": "RAW MODEL ACCESS: send the prompt with NO Hermoso system prompt — the model answers as itself rather than as an ad copywriter. Use it whenever the ask is not marketing copy (analysis, code, extraction, a plain question). Default false: the copywriter framing is applied.",
+  "type": "boolean"
+}
    • changedOutput schema / (root)
      Previous value: -{
-  "$schema": "http://json-schema.org/draft-07/schema#",
-  "additionalProperties": false,
-  "properties": {
-    "creditsUsed": {
-      "description": "credits billed for this generation",
-      "type": "number"
-    },
-    "model": {
-      "description": "the writing model label",
-      "type": "string"
-    },
-    "text": {
-      "description": "the generated text",
-      "type": "string"
-    }
-  },
-  "type": "object"
-}New value: +null
  2. Addedv0.1.15

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only give safety/scope hints (readOnly=false, openWorld=true, idempotent=false), but the description adds substantial behavior: a default house system prompt is applied and what it does, how raw:true suppresses it, the model source (hermoso_capabilities), the default orchestrator, and that the call is paid by length. That is real disclosure beyond structured fields.

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?

Front-loaded with the core purpose and scope, and each clause earns its place (use cases, alternative path, default-vs-raw behavior, cost). The model enumeration and parentheticals are slightly dense but not wasteful.

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?

With no output schema needed for a free-text generator and annotations covering safety, the description supplies the operationally important details (raw default, model source, cost, no ad assembly). It could note latency/response-size behavior, but nothing essential for correct invocation is missing.

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 the bar is a baseline 3, but the description goes further by explaining that model ids come from hermoso_capabilities, that omission picks the default Claude orchestrator, and by elaborating the raw default behavior—adding meaning the schema's terse text does not fully carry.

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?

States a specific verb (generate text) and resource (the writing-model catalog), enumerating concrete use cases (ad copy, hooks, scripts, rewrites, brainstorms). It explicitly contrasts itself with plan_ad -> render_ad for a finished on-brand creative, so an agent can route without opening the schema.

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?

Names the alternative path explicitly ('for a finished on-brand creative use plan_ad -> render_ad') and states the condition that selects raw:true ('whenever the ask is not marketing copy'). Both the when-to-use and when-not are covered.

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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