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@aiwerk/mcp-server-ghl

@aiwerk/mcp-server-ghl

by AIWerk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

brand_boards_get_brand_boards_by_location

Read-onlyIdempotent

Retrieve brand boards for a specific location, with options to filter by name, paginate results, or include deleted entries.

Instructions

Get Brand Boards

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "brand_boards_get_brand_boards_by_location"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of brand boards to return
offsetNoNumber of brand boards to skip for pagination
searchNoSearch term to filter brand boards by name
deletedNoInclude deleted brand boards in results
locationIdNoDefaults to GHL_LOCATION_ID when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

D1.9/5.0
Behavior2/5

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

Annotations already provide substantial behavioral information (readOnlyHint=true, idempotentHint=true, destructiveHint=false). The description adds nothing beyond a bare statement, providing no context about default location behavior, pagination, or what is returned. Since the description adds no value beyond annotations, this scores low.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely brief (one sentence), which is efficient but under-specified. It lacks necessary detail to be considered well-structured. While it is front-loaded, it does not earn its place by conveying any useful information beyond the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must explain return values and any important behaviors. It does neither. The tool has 5 optional parameters with implications (pagination, filtering, location defaulting), none of which are mentioned. The description is completely inadequate for effective use.

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?

The input schema covers all 5 parameters with descriptions (100% coverage). Per the rubric, a baseline of 3 is appropriate when the schema fully documents parameters. The description contributes no additional semantic 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.

Purpose2/5

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

The description 'Get Brand Boards' is essentially a restatement of the tool name. It names a verb and resource but does not specify the 'by location' aspect or how this differs from sibling tools like brand_boards_get_brand_board_by_id. It lacks the specificity needed to distinguish this tool from alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description does not indicate contexts where this tool is appropriate, nor does it mention any exclusions or prerequisites. An agent is left to infer from the tool name alone.

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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