Skip to main content
Glama

finance_due_diligence_packet

Performs finance due diligence by executing domain agent actions. Provide a free-text objective and optional structured inputs.

Instructions

Run the finance domain agent action finance_due_diligence_packet.

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 are provided, so the description bears full responsibility. It notes that the tool routes through a domain-agent dispatcher with JWT/tenant/company scope, which adds some context. However, it does not disclose whether the tool performs read-only or destructive actions, what side effects occur, or any rate limits or authentication requirements beyond the implied scope.

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 very concise: a single sentence stating the action, a line about routing, and a clear Args section. Every element serves a purpose without redundancy. The structure is front-loaded with the tool's name and immediately explains what it does.

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?

While an output schema exists, the description does not explain what the tool returns (e.g., a packet document, summary). For a tool that runs an agent action, more context about the expected outcome and behavior would be beneficial. The description is adequate but leaves gaps about the result.

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 schema has 0% description coverage, but the description adds meaningful semantics for both parameters: 'message' is described as 'Free-text objective for the action', and 'inputs' as 'Optional JSON string of structured inputs for the action'. This clarifies the purpose and format beyond the schema's default values and types.

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

Purpose3/5

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

The description states it runs a finance due diligence packet agent action, which indicates a specific function, but it lacks differentiation from sibling tools like 'finance_due_diligence' or 'finance_data_room_collation_packet'. The verb 'Run' is vague, and the resource 'due diligence packet' is not explained in terms of what it produces or modifies.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, context, or scenarios where this tool is preferred over siblings. The agent is left to infer usage 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.

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