Skip to main content
Glama
manganate006

OpenLMNP

Generate Tax Return

generate_tax_return

Produces the LMNP tax return PDF (forms 2031, 2033-A to 2033-G) for a given fiscal year, recalculating as needed, and returns the PDF path and key amounts summary.

Instructions

Génère la liasse fiscale LMNP au format PDF (formulaires 2031, 2033-A à 2033-G) pour un exercice fiscal donné. L'exercice est recalculé avant la génération si nécessaire. Retourne le chemin du PDF généré et un résumé des montants clés de la déclaration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
Behavior3/5

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

Mentions fiscal year recalculation before generation, a key behavioral aspect, but lacks details on side effects (e.g., does recalculation modify data?) and no annotations to provide safety context.

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?

Two sentences, front-loaded with core action, no wasted words.

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

Completeness5/5

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

Covers purpose, input, side effect (recalculation), and output (path and summary), sufficient for a simple tool with one parameter and no output schema.

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?

Single parameter 'year' is explained implicitly via context (fiscal year), but schema has no descriptions; description adds moderate clarity.

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

Purpose5/5

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

Description clearly states it generates LMNP tax return PDF with specific forms (2031, 2033-A to 2033-G) for a given fiscal year, which is precise and distinguishes from other tools.

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?

No explicit guidance on when to use this over related tools like compute_fiscal_year or generate_fec; context implies it's for final declaration but not stated.

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/manganate006/openlmnp'

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