Skip to main content
Glama

dpe_logement

Get DPE for existing French homes by postal code. Optionally add an address to refine results including energy and GHG labels, surface area, consumption, and date.

Instructions

Diagnostics de Performance Énergétique (DPE) de logements existants (ADEME).

Renvoie étiquette énergie (A→G), étiquette GES, surface, consommation et date du diagnostic. Filtre par code postal, affinable par une adresse.

Args: code_postal: code postal sur 5 chiffres (ex. « 75011 »). adresse: optionnel — texte d'adresse pour affiner (ex. « 48 rue de Montreuil »).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adresseNo
code_postalYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses output fields and source (ADEME) but lacks details on behavior such as error handling, rate limits, or authentication needs. For a read-only query tool, the description is adequate 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?

Description is concise with four lines plus an Args section that reiterates parameters with examples. Every sentence adds value, though the Args section partially duplicates schema info. Overall well-structured and front-loaded.

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

Completeness4/5

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

Tool has only two parameters and an output schema (present but not shown). Description explains key return fields. For its simplicity, coverage is good; lacks only minor details like error conditions or pagination.

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 coverage is 0%, so description compensates by explaining both parameters: code_postal as 5-digit zip code with example, adresse as optional text to refine. Adds meaningful context beyond the schema's type and default values.

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 returns DPE diagnostics with specific output fields (energy label, GES label, surface, consumption, date) and filtering by postal code and optionally address. This verb+resource definition distinguishes it from sibling tools like geocode_address or risques_immobilier.

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?

Description implies usage context by mentioning filtering by postal code and address, but does not explicitly state when to use this tool versus alternatives, nor provides exclusions or prerequisites. Sibling tools differ in function but no comparative guidance given.

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/GabMJ23/nyambot-mcp'

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