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Hermoso

by io.github.hermoso-ai

Remember a fact

remember

Save a durable fact or PREFERENCE about the brand, audience, or the user’s creative TASTE (e.g. “audience is first-time homebuyers”, “prefers bold lime accents”, “always captions off”) into the workspace Memory so it shapes FUTURE ads. For lasting things, not one-off requests. Merges into the existing Memory (never overwrites); de-dupes on identical text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesthe fact/preference, concise
categoryNoshort bucket: Brand, Audience, Taste, Do, Don’t, or Preference (default General)

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only indicate write behavior (readOnlyHint false). The description adds critical behavioral details: 'Merges into the existing Memory (never overwrites); de-dupes on identical text.' This explains side effects and idempotency, going well beyond what annotations provide.

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 a single dense sentence that packs the action, examples, scope, and key behaviors without excess. The most important information (save durable fact) comes first, and examples are woven in effectively. No wasted words.

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 tool with only 2 parameters and no output schema, the description covers everything an agent needs: purpose, scope, examples, and merge/duplicate behavior. It is self-contained and leaves no ambiguity about invocation.

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 parameters are documented. The description adds semantic value by providing examples of what constitutes a 'fact' or 'preference' and clarifies the purpose of the 'text' field. It doesn't explicitly mention 'category', but the schema handles that. The examples enhance understanding beyond the schema's bare 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 states a specific action (save) and resource (durable fact/Preference into workspace Memory) with concrete examples. It clearly distinguishes this from siblings like 'forget' by framing it as storing lasting facts, and from general-purpose storage tools by specifying it shapes future ads.

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?

It provides clear guidance on when to use: 'For lasting things, not one-off requests.' This implies a contrast with ephemeral or temporary facts, helping the agent decide. It doesn't explicitly name an alternative tool, but the context is sufficient.

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