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Hermoso

by io.github.hermoso-ai

List the tabs in a Google Sheet

list_sheet_tabs
Read-only

The tabs in a Google Spreadsheet, each with its name, numeric sheetId, row/column count and position. Call this BEFORE naming a tab in update_sheet / clear_sheet_range / manage_sheet_tabs / format_sheet, and before proposing to delete one — it is how you learn what the file actually contains instead of guessing at a name. Read-only, free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sheetUrlNoa Google Sheets URL — the id is extracted from it
spreadsheetIdNothe spreadsheet id (from create_sheet, or list_drive_files for one the user picked)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false, so the description doesn't need to repeat that. It adds value by specifying the exact data returned (name, sheetId, row/column count, position) and explicitly stating 'Read-only, free,' which goes beyond annotation (especially the 'free' cost hint). This extra context is useful without contradicting annotations.

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?

Three sentences, each with a clear purpose: the first describes the output, the second gives usage guidance with named alternatives, and the third confirms safety and cost. No filler or repetition; the most critical info (purpose) is front-loaded.

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 simple read-only list tool, this is complete: it specifies the inputs (via schema), the outputs (fields listed in description), the safety profile (via annotations + description), and the proper usage context (before dependant tools). Even without an output schema, the description conveys enough for an agent to call and interpret the result correctly.

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% — both sheetUrl and spreadsheetId have detailed descriptions explaining their origin and usage. The tool description does not add any further meaning to the parameters, so it relies entirely on the schema. Per the rubric, with full schema coverage, a baseline of 3 is appropriate.

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 verb ('list') and resource ('tabs in a Google Sheet'), and enumerates the returned fields (name, numeric sheetId, row/column count, position). While it doesn't explicitly contrast with sibling list_* tools, it clearly positions itself as the discovery/pre-requisite tool for tab operations, making its purpose unambiguous.

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?

It explicitly instructs to call this BEFORE naming a tab in update_sheet / clear_sheet_range / manage_sheet_tabs / format_sheet, and before proposing deletion. This nails the when-to-use and names the dependent tools, effectively differentiating it from alternatives. The phrase 'instead of guessing at a name' also clarifies the context of use.

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