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Glama

Look up an Admin API endpoint

lookup-endpoint
Read-onlyIdempotent

Look up Tiendanube Admin API endpoints by path, resource, or keywords to retrieve the method, full URL, required OAuth scope, and reference page offline while writing or reviewing API calls.

Instructions

Look up Tiendanube / Nuvemshop Admin API endpoints by path, resource or keywords: method, path, full URL with version and store_id, the OAuth scope it needs and the reference page. Works offline from an index of the 2025-03 reference. Use it when writing or reviewing API calls.

Input Schema

NameRequiredDescriptionDefault
limitNoMax results for keyword search (default 15)
queryYesA path ("/orders/{id}/fulfill", "/products/123/variants"), a resource name ("Fulfillment Order") or keywords ("tracking event", "custom fields product")
methodNoHTTP method

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new context beyond that: the results come from an offline index pinned to the 2025-03 reference, which tells the agent about staleness and no-network behavior. It does not mention result limits or no-match behavior, which keeps it below a 5.

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?

Two sentences, front-loaded with the lookup modes and followed by the return fields and the usage cue. Every clause carries information; the return-field list earns its place because there is no output schema.

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 usefully enumerates what comes back (method, path, full URL with version and store_id, OAuth scope, reference page) and notes the offline/versioned index. It leaves open whether matching is exact or fuzzy and what an empty result looks like, which are the remaining gaps for a search tool.

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%, and the schema already spells out the query forms, the method enum, and the limit default/max. The description's "by path, resource or keywords" restates what the query parameter documentation already provides, adding no syntax or behavior beyond it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Look up ... Admin API endpoints") plus the three lookup modes (path, resource, keywords) and the fields returned. The resource type (endpoints) separates it implicitly from siblings like search-docs and lookup-scope, but no sibling is named explicitly.

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?

"Use it when writing or reviewing API calls" gives a clear triggering context, and the path/resource/keyword enumeration hints at valid input styles. It stops short of stating when to prefer search-docs or lookup-scope instead, so the routing decision is left partly to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.