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Glama

Hermoso

by io.github.hermoso-ai

List errors users hit

list_errors
Read-only

The errors actually recorded against this workspace, GROUPED by fingerprint — the same failure at the same call site is one row with a hit count and first/last seen, sorted defects-first. Each row says whose side it is: ours (a defect worth fixing), user (a refusal we deliberately authored, e.g. not-connected or out-of-credits), or unknown (a vendor 4xx we cannot attribute — never guessed). Free text, tokens, emails and creative are redacted before anything is stored, so an input echo shows shapes and lengths, not content. Filter by surface (http/mcp/agent/job/client) or kind. Read-only, 0 credits. Scoped to your own workspace; an operator whose client carries the admin key sees every account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo'ours' = a defect; 'user' = a refusal we authored; 'unknown' = we could not tell
limitNohow many groups to return (default 50, max 200)
sinceNoISO timestamp — only groups last seen at or after this
surfaceNowhere it happened: http (an API route), mcp (an agent tool), agent (the in-app Studio agent), job (an async render/publish), client (a browser crash)

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare read-only and non-destructive behavior. The description adds much more: grouping by fingerprint, hit count and first/last seen, defects-first sorting, the ours/user/unknown classification policy with 'never guessed', redaction of free text/tokens/emails/creative, input echoes showing shape not content, and scope behavior. This is far 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 dense but every sentence earns its place: core grouping and row semantics, classification values, redaction behavior, filter options, and access scope. It front-loads the main purpose and uses no filler. The one long sentence is still well-structured and immediately informative.

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?

With no output schema, the description compensates by explaining the row model (fingerprint groups, hit count, first/last seen), sort order, classification meanings, redaction effects, filter opportunities, credit cost, and permissions. An agent has enough to call the tool correctly and interpret the result without further documentation.

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?

The input schema already has 100% description coverage, so the baseline is 3. The tool description enriches the `kind` enum with concrete examples ('not-connected or out-of-credits', 'vendor 4xx') and the 'never guessed' caveat, and it explicitly names the filterable surfaces. It does not add meaning for `limit` or `since`, so a modest boost to 4 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 opens with a precise definition: 'errors actually recorded against this workspace, GROUPED by fingerprint' and explains the grouping unit, row contents, and sort order. It clearly distinguishes itself from sibling `error_detail` by describing an aggregate, classified list rather than a single error's detail. The verb and resource are unambiguous.

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 gives clear context: read-only, 0 credits, scoped to the current workspace, with optional filtering by surface or kind. It also notes the admin-key expansion to all accounts. However, it never explicitly contrasts with the sibling `error_detail` or states when not to use this tool, so it falls short of full routing guidance.

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