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Evan-Crx

permisapi-mcp

get_existing_buildings

Distinguish vacant land from built parcels by listing existing cadastral buildings on a permit parcel. Returns building count by type (heavy, light, other) and vacancy flag.

Instructions

Liste les bâtiments cadastraux déjà construits sur la parcelle du permit. Use case CRITIQUE marchand de biens : distinguer parcelle nue (vraie construction neuve, value-add max) vs parcelle bâtie (extension/rénovation, value-add moindre). Retourne nb_batiments total + décompte par type (bâti dur / bâti léger / autre) + flag parcelle_nue boolean + détails individuels (id Etalab, type label FR, centroïde, dates création/MAJ cadastre). Source : cadastre.data.gouv.fr via Etalab (DGFiP). Plan Pro+ uniquement. Coût 1 unité quota. 404 si le permit n'a pas de polygone cadastre disponible (rare, ~15% des permits).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
num_paYesIdentifiant Sitadel unique (ex PC07404021K1).
Behavior4/5

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

No annotations are provided, so the description fully carries the burden. It discloses the output (nb_batiments, breakdown, flag, details), data source, plan restriction (Pro+), cost (1 unit), and error behavior (404). It does not mention mutation or safety, but as a read tool, this is sufficient.

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 moderately long but each sentence provides distinct value (purpose, use case, output details, source, limitations, error). It is front-loaded with the core purpose.

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?

Given no output schema, the description thoroughly explains the return values, including counts, flag, and individual details. It also covers source, plan restriction, cost, and error case, making it complete for agent invocation.

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 100% for the single parameter 'num_pa', which is already described in the schema as 'Identifiant Sitadel unique'. The description adds no additional semantic details beyond the schema, so baseline 3 is appropriate.

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?

The description explicitly states the tool lists existing buildings on a parcel for a permit, with specific verb 'Liste' and resource 'bâtiments cadastraux déjà construits'. It distinguishes from siblings by detailing a critical use case (marchand de biens) and output specifics.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool (e.g., assessing if a parcel is bare or built) and mentions a specific use case. However, it does not explicitly state when not to use or name alternatives among sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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