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List your brand imports

list_brands

Your brand imports on refs.video (refs.video/saved → Brandprint): each X account you imported, with its progress and film count. Private to you. Pass an id or handle to get_brand for the brand kit and every film.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

No annotations exist, so the description carries the load; it discloses privacy ("Private to you") and the contents of each entry, which is useful. It does not state ordering, pagination, or whether an empty list is possible, and read-only behavior is only implied by the verb "list".

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 compact sentences with the resource and return contents front-loaded, followed by the routing hint. No filler or repetition.

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 specifies the shape of the result (each account with progress and film count) and the privacy scope. Minor gaps around ordering and pagination keep it from a 5.

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 two schema parameters are analytics-only boilerplate (context, llm_model) and are fully documented at 100% coverage, so there is no domain parameter for the description to explain. Nothing is missing, but the description adds no value over the schema here.

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?

Specific verb and resource: it lists the user's brand imports on refs.video/saved, describing exactly what each entry contains (X account, progress, film count). It also distinguishes itself from the sibling get_brand by assigning that tool a different job (brand kit and films).

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?

Routes the agent explicitly: pass an id or handle to get_brand to get the brand kit and every film, which is a clear alternative-selection rule. What's missing is a direct statement of when to call this tool itself (e.g. to discover which brands were imported), though that is strongly implied.

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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