idealista
Query Idealista API via idealista-cli (OAuth2 client credentials).
Setup & Installation
Install command
clawhub install quifago/idealistaIf the CLI is not installed:
Install command
npx clawhub@latest install quifago/idealistaOr install with OpenClaw CLI:
Install command
openclaw skills install quifago/idealistaor paste the repo link into your assistant's chat
Install command
https://github.com/openclaw/skills/tree/main/skills/quifago/idealistaWhat This Skill Does
Queries the Idealista real estate API using idealista-cli with OAuth2 client credentials. Supports searching property listings by location, operation type, and property type, and computing price statistics across results.
Handles OAuth2 token acquisition and caching automatically, so queries run without manual authentication steps each time.
When to Use It
- Search for apartments for sale within a radius of given coordinates
- Find rental homes under a price limit in a Spanish city
- Compute average sale prices grouped by property type in an area
- Retrieve all listing pages for a broad area search
- Ask an agent in natural language to find a flat matching specific criteria
View original SKILL.md file
# idealista This skill documents how to query the Idealista API using the local `idealista-cli`. ## Local project location - CLI source (example): `~/idealista-cli` ## Credentials (client_id / client_secret) Idealista uses OAuth2 **Client Credentials**. Use environment variables (recommended): - `IDEALISTA_API_KEY` = `client_id` - `IDEALISTA_API_SECRET` = `client_secret` Example: ```bash export IDEALISTA_API_KEY="<CLIENT_ID>" export IDEALISTA_API_SECRET="<CLIENT_SECRET>" ``` Or persist them via the CLI: ```bash python3 -m idealista_cli config set \ --api-key "<CLIENT_ID>" \ --api-secret "<CLIENT_SECRET>" ``` Config file path: - `~/.config/idealista-cli/config.json` Token cache: - `~/.cache/idealista-cli/token.json` ## Common commands Get a token: ```bash python3 -m idealista_cli token python3 -m idealista_cli token --refresh ``` Search listings: ```bash python3 -m idealista_cli search \ --center "39.594,-0.458" \ --distance 5000 \ --operation sale \ --property-type homes \ --all-pages \ --format summary ``` Compute stats: ```bash python3 -m idealista_cli avg \ --center "39.594,-0.458" \ --distance 5000 \ --operation sale \ --property-type homes \ --group-by propertyType ``` ## Example queries (natural language) Use these as “prompt” examples for an agent that calls the CLI: - "Find a flat in A Coruña under 200.000€" - "Tell me the average price of a house around here: 39°34'33.5\"N 0°30'10.0\"W" - "Búscame un apartamento de 3 habs en Tapia de Casariego para comprar"
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Search for apartments for sale within a radius of given coordinates
- 1Search for apartments for sale within a radius of given coordinates
- 2Find rental homes under a price limit in a Spanish city
- 3Compute average sale prices grouped by property type in an area
- 4Retrieve all listing pages for a broad area search
- 5Ask an agent in natural language to find a flat matching specific criteria
Query Idealista API via idealista-cli (OAuth2 client credentials).
Security Audits
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