Skip to main content
Glama
van0219

ReAI MCP Server

by van0219

reai_generate_columnar

Generate a complete columnar LPL report package (filter form, list view, custom fields, CSV) for FSM migration by providing a report name, business class, and field definitions.

Instructions

Generate Columnar LPL code package for FSM. Produces 4 files: .form (filter form), .list (columnar list with charts), .field (custom derived fields), and .csv (replication set import). Provide the report name, business class, and field definitions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYesArray of field definitions for the report
report_nameYesReport name in PascalCase without spaces (e.g., "GLTransactionDetail", "AssetDepreciation")
business_classYesPrimary FSM business class (e.g., "GLTransactionDetail", "AssetTransaction", "PayablesInvoice")
Behavior3/5

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

No annotations are provided, so the description carries the burden. It does disclose the tool's output granularity (4 specific files) and that it's a generation/write operation. However, it doesn't mention whether it overwrites existing files, requires any environment setup, or produces side effects. For a generation tool this is acceptable but not rich.

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 compact, front-loaded with the action and output, and ends with required inputs. Two sentences, no filler. Slightly verbose on the file enumeration but each file type with its parenthetical purpose is informative.

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 generation tool with 3 fully-documented parameters, the description covers the essentials: what it does, what it produces, and what to provide. However, it doesn't describe return/output behavior beyond file names, or any validation rules. Adequate but leaves an agent guessing about what happens after generation (where files go, how to access them).

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 description coverage is 100%, with each parameter well-described (PascalCase format, e.g., values, array structure). The description adds that field definitions are needed but doesn't add meaning beyond the schema. Baseline 3 applies since the schema does the heavy lifting and the description doesn't contradict or extend it.

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 verb ('Generate') and specific resource ('Columnar LPL code package for FSM'). It enumerates the 4 files produced, which is specific and useful. It doesn't explicitly differentiate from sibling tools (which appear to be stats/analysis tools), but the core purpose is clear.

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

Usage Guidelines3/5

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

The description provides inputs needed ('Provide the report name, business class, and field definitions') which implies use cases. It doesn't offer explicit when-to-use vs when-not-to-use guidance or mention alternatives, but the sibling tools are sufficiently different (stats, search, modules) that context is reasonably clear. It lacks exclusions or prerequisites.

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/van0219/reai-mcp'

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