Skip to main content
Glama

engineering_search_project_drawings

Search project drawings by describing your objective in free text or providing structured inputs. Returns relevant engineering drawings.

Instructions

Run the engineering domain agent action search_project_drawings.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
inputsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations exist, so the description must fully disclose behavior. It mentions routing through a dispatcher and JWT/tenant/company scope, indicating auth requirements. However, it does not state whether the tool is read-only, destructive, or any side effects. For a search action, it likely is read-only, but that's not explicit.

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

Conciseness4/5

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

The description is concise with one sentence and a parameter list. It is front-loaded with the purpose and includes the args in a clear format. There is no redundant information, though the routing detail could be considered secondary.

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

Completeness3/5

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

For a simple search tool with an output schema (though not shown), the description is mostly adequate but missing details on output format or what 'search_project_drawings' entails (e.g., returns drawing IDs, metadata?). It hints at scope but doesn't explain the domain-agent dispatcher or typical result structure, leaving gaps for an agent to fully understand the tool's 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?

Schema coverage is 0%, so the description provides the only parameter documentation. It adds minimal but helpful descriptions: 'message' as free-text objective and 'inputs' as optional JSON string. This adds meaning beyond the bare schema fields, but the descriptions are quite generic and lack detail on expected format or constraints.

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?

The description clearly states the tool searches project drawings within the engineering domain agent. It specifies the action name 'search_project_drawings', making the purpose clear. However, it does not differentiate from similar search tools like 'search_documents', so it loses a point for sibling differentiation.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. It mentions routing and scope but does not provide context about appropriate use cases, prerequisites, or when not to use it.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RPasquale/lightbulb-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server