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Hermoso

by io.github.hermoso-ai

Pull competitor ads

pull_competitor_ads
Read-only

THE FAST PATH for "show me the ads is running" — one named brand’s real live ads from the META (Facebook/Instagram) ad library, deduped, sorted, with the right page resolved. A single call, back in a few seconds. Prefer this over research_ads whenever the brand is named. Meta only, deliberately: it has by far the richest creative and is what people mean by "their ads". For Google or LinkedIn specifically, use search_google_ads or search_linkedin_ads. Spends credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo'longest_running' (default) etc.
limitNomax ads per platform (default 30)
domainNothe advertiser domain
countryNo2-letter, default 'US'
companyNameNothe advertiser name

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The annotations already mark this as read-only and non-destructive, and the description adds meaningful behavioral context: the call spends credits, returns deduped and sorted results, and resolves the correct page. This goes beyond the structured safety hints without contradicting 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 longer than the minimum but every sentence earns its place: it states the use case, scope, alternatives, and credit cost. The opening phrase is front-loaded and scannable, though the tone is slightly promotional.

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, the description still communicates what the agent should expect conceptually: real live ads, deduped, sorted, and with the page resolved. It also covers scope, alternatives, and side effects, leaving only fine-grained return-field details unspecified.

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

Parameters3/5

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

Schema description coverage is 100%, so the heavy lifting is done by the input schema. The description reinforces that the tool targets a 'named brand' and mentions sorting, but it does not add substantial parameter-level meaning beyond what the schema already provides.

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 clear, specific statement: it is the fast path for showing one named brand's real live ads from the Meta ad library, deduped, sorted, and with the right page resolved. It names concrete alternatives like research_ads and search_google_ads, making the tool's niche unmistakable.

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?

The description explicitly says to prefer this tool over research_ads whenever the brand is named, and directs users to search_google_ads or search_linkedin_ads for Google or LinkedIn. This gives an agent clear routing rules with no need for inference.

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

A3.8/5.0
Disambiguation3/5

The descriptions are exceptionally detailed and cross-reference one another (e.g. post_edit vs finish_video vs edit_video), which genuinely helps, but 168 tools still contain tight clusters—video creation/editing, scheduling, and post-publishing—where misselection is easy. Many tools also reference hidden companions not in the visible set, adding ambiguity.

Naming Consistency4/5

The overwhelming majority follow a clear verb_noun snake_case convention (post_to_x, search_x, list_x, create_x, update_x). Minor deviations like store_get, billing_status, error_detail, and the hermoso_ prefix break the pattern slightly but do not obscure it.

Tool Count1/5

At 168 tools this is far beyond the 50+ threshold, and regardless of how broad the platform's purpose is, the sheer number makes the set hard to navigate. The server mitigates with groups and find_tools/call_tool, but the count itself is extreme.

Completeness4/5

The set covers a full marketing lifecycle—research, planning, creation, publishing, scheduling, measurement, billing, and file management—with no major workflow gaps. Some referenced tools like list_shopify_products and manage_meta_post are not in the visible list, but find_tools and call_tool are explicitly designed to close that gap.

Resources