Skip to main content
Glama

legal_law_firm_growth_loop

Execute a law firm growth loop by providing a free-text objective and optional structured inputs. Automates domain-specific agent actions to drive firm growth.

Instructions

Run the legal domain agent action law_firm_growth_loop.

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?

With no annotations, the description alone must disclose behavioral traits. It reveals routing through a domain-agent dispatcher under JWT/tenant/company scope, but fails to mention side effects, data mutations, or other behavioral characteristics of the growth loop. This is minimal disclosure for a potentially complex action.

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 short and front-loaded with the primary purpose. The parameter descriptions are in a clear docstring format. It avoids unnecessary words, though the arg descriptions could be more integrated for slightly better readability.

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?

Given that the tool is a generic wrapper to run a domain action, the description provides the minimum necessary to invoke it. However, it lacks context on what the growth loop does, expected outcomes, or how the response relates to the action. An output schema exists but is not mentioned, so completeness is adequate but not rich.

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 must compensate. It adds basic semantics: 'message' is described as 'Free-text objective' and 'inputs' as 'Optional JSON string of structured inputs'. This provides more meaning than the bare schema, but lacks detail on expected format or examples, leaving room for ambiguity.

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 'Run the legal domain agent action law_firm_growth_loop', providing a specific verb and resource. It distinguishes itself from sibling legal tools by specifying 'growth loop', though it does not explicitly differentiate from similar legal action tools.

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, nor any when-not-to-use scenarios. It simply describes what the tool does, leaving the agent to infer appropriate usage context without explicit direction.

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