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lightbulb-mcp

lightbulb-mcp

by RPasquale
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

procurement_spend_analysis

Destructive

Analyze procurement spend data to identify trends, optimize costs, and inform sourcing decisions.

Instructions

Run the procurement domain agent action spend_analysis.

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.

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": "procurement_spend_analysis"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already convey destructiveHint=true, openWorldHint=true, and non-idempotent behavior, so the description does not need to repeat those. It adds useful context about routing through the domain-agent dispatcher under the JWT, tenant, and company scope, but it does not disclose what the action may change or what side effects to expect.

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 compact, front-loaded with the action, and every sentence earns its place. The scope note and args list are directly useful with no filler.

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?

The tool has an output schema and annotations, so return values and safety profile are partially covered. However, the description does not explain what spend_analysis actually analyzes, what structured inputs are valid, or when to prefer this over similar tools, leaving the agent with only the name and free-text message to infer intent.

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?

Schema description coverage is 0%, so the description carries the burden of explaining parameters. It does so clearly: 'message' is a free-text objective and 'inputs' is an optional JSON string of structured inputs. This is meaningful beyond the bare schema, though it does not detail the JSON structure.

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 uses a specific verb and resource: 'Run the procurement domain agent action spend_analysis.' This clearly identifies what the tool does. However, it does not distinguish it from similar siblings like commerce_spend_analysis or dispatch_domain_agent.

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?

The description provides no guidance on when to use this tool versus alternatives such as commerce_spend_analysis or other procurement actions. It mentions routing and scope but not selection criteria, prerequisites, or exclusions.

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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