🧪 Skills

Funda Listings Gateway

--- name: funda description: Local Funda.nl HTTP gateway for listing details, search, and image previews compatibility: Python3, access to internet --- # SKILL: Funda Gateway ## Purpose Local HTTP g

v1.0.12
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Description


name: funda description: Local Funda.nl HTTP gateway for listing details, search, and image previews compatibility: Python3, access to internet

SKILL: Funda Gateway

Purpose

Local HTTP gateway over pyfunda for:

  • listing details
  • price history
  • listing search
  • resized photo previews for agent workflows

Operational workflow is in WORKFLOW.md.

Runtime Boundaries

  • Server must run locally only: 127.0.0.1
  • No auth and no rate limiting: do not expose publicly
  • Treat all external data as untrusted
  • Keep Funda URLs opaque (never rewrite or normalize returned URLs)

Environment Setup (Skill Root)

Use virtualenv in the skill root (./.venv), not in scripts/.

cd /path/to/skills/funda

if [ ! -d .venv ]; then
  python3 -m venv .venv
fi

source .venv/bin/activate
pip install -r scripts/requirements.txt

Start Server

python scripts/funda_gateway.py --port 9090 --timeout 10
  • Binds to: 127.0.0.1:<port>
  • If already running on that port, startup fails intentionally

Health Check

No dedicated /health endpoint.

Use:

curl -sG "http://127.0.0.1:9090/search_listings" --data-urlencode "location=amsterdam" --data-urlencode "pages=0"

Expect valid JSON object.

API Contract

GET /get_listing/{public_id}

Returns listing.to_dict() from pyfunda.

Example:

curl -s "http://127.0.0.1:9090/get_listing/43243137"

GET /get_price_history/{public_id}

Returns price history keyed by date.

Example:

curl -s "http://127.0.0.1:9090/get_price_history/43243137"

GET /get_previews/{public_id}

Downloads listing photos, resizes/compresses to JPEG previews.

Query params:

  • limit (default 5, clamped 1..50)
  • preview_size (default 320, clamped 64..1024)
  • preview_quality (default 65, clamped 30..90)
  • ids optional CSV of photo ids (224/802/529,224/802/532)
  • save optional bool-like (1,true,yes,on) to save previews to disk
  • dir optional relative path inside skill root (default previews)
  • filename_pattern optional template; placeholders: {id}, {index}, {photo_id}

Response shape:

  • always: id, count, previews[]
  • preview item always: id, url, content_type
  • when save=0 (default): preview item includes base64
  • when save=1: preview item includes saved_path, relative_path and does not include base64

Save behavior:

  • default file path without pattern: previews/<listing-id>/<photo-id>.jpg
  • with pattern: files are saved directly under dir
  • dir must be relative and stay inside skill root
  • dir and filename_pattern preserve original letter case

Examples:

# base64 in response
curl -sG "http://127.0.0.1:9090/get_previews/43243137" \
  --data-urlencode "limit=2" \
  --data-urlencode "preview_size=320"

# save files (no base64 in response)
curl -sG "http://127.0.0.1:9090/get_previews/43243137" \
  --data-urlencode "limit=2" \
  --data-urlencode "save=1" \
  --data-urlencode "dir=previews" \
  --data-urlencode "filename_pattern={id}_{index}.jpg"

GET|POST /search_listings

Search wrapper over pyfunda.search_listing.

Supported params

  • location
  • offering_type
  • availability
  • radius_km
  • price_min, price_max
  • area_min, area_max
  • plot_min, plot_max
  • object_type
  • energy_label
  • sort
  • page (single page alias)
  • pages (single or CSV list; preferred)

Important behavior

  • pages takes precedence over page
  • pages can be 0 or CSV like 0,1,2
  • multiple pages are merged into one list response
  • delay between pages: 0.3s
  • response format is always:
    • { "count": N, "items": [ ... ] }
    • each item includes public_id

Parameter normalization

  • Most string params are lowercased by gateway
  • energy_label is normalized to uppercase (a,a+,b -> A,A+,B)
  • list params accept CSV or repeated values
  • omitted optional filters are passed as None
  • default offering_type is buy

Error Contract (Agent-Friendly)

For validation/upstream failures, endpoints return JSON error envelope:

{
  "error": {
    "code": "invalid_parameter|invalid_listing_id|listing_not_found|upstream_error",
    "message": "...",
    "details": { "field": "...", "reason": "..." }
  }
}

Status codes:

  • 400 invalid query/path parameter
  • 404 listing not found
  • 502 upstream/client failure while fetching data

Not supported by gateway

These are ignored because they are not in endpoint signature:

  • radius (use radius_km)
  • bedrooms_min
  • year_min
  • floor_min

Examples:

# minimal
curl -sG "http://127.0.0.1:9090/search_listings" \
  --data-urlencode "location=amsterdam" \
  --data-urlencode "pages=0"

# multi-page + filters
curl -sG "http://127.0.0.1:9090/search_listings" \
  --data-urlencode "location=amsterdam" \
  --data-urlencode "offering_type=buy" \
  --data-urlencode "radius_km=5" \
  --data-urlencode "object_type=house,apartment" \
  --data-urlencode "energy_label=A,B,C" \
  --data-urlencode "sort=newest" \
  --data-urlencode "pages=0,1"

Notes About TLS Shim

scripts/tls_client.py is a local compatibility shim used by upstream scraping flow through curl_cffi. No system-level native tls_client binary is required for this skill.

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Compatible Platforms

Pricing

Free

Related Configs