Windmill

Context for GOAT's Windmill instance. Use the Windmill MCP tools for API calls; this skill provides domain knowledge.

Setup

• URL / Web UI: WINDMILL_URL in .env (local dev: http://localhost:8110)
• Workspace: goat
• Token: WINDMILL_TOKEN in .env — never hardcode it

Folder Structure

All scripts live under f/goat/:

• f/goat/tools/ — Analytics tools (synced from goatlib, run by the processes service)
• f/goat/tasks/ — Background tasks (thumbnails, S3 sync, etc.)

Tools — do not hardcode the list

The tool set changes often. The single source of truth is the registry: packages/python/goatlib/src/goatlib/tools/registry.py (TOOL_REGISTRY). Scripts under f/goat/tools/ are auto-generated from it via python -m goatlib.tools.sync_windmill.

To see the current tools (grouped by category, with hidden/beta/worker flags), run from repo root:

uv run python -c "
from itertools import groupby
from goatlib.tools.registry import TOOL_REGISTRY
for cat, items in groupby(sorted(TOOL_REGISTRY, key=lambda t: t.category), key=lambda t: t.category):
    print(f'## {cat}')
    for t in items:
        flags = [f for f, on in (('hidden', t.toolbox_hidden), ('beta', t.beta), (f'worker={t.worker_tag}', t.worker_tag != 'tools')) if on]
        print(f\"  {t.windmill_path}{'  [' + ', '.join(flags) + ']' if flags else ''} — {t.description}\")
"

Categories: geoprocessing, data_management, geoanalysis, accessibility_indicators, data (the data category is toolbox-hidden internal tools: layer import/update/delete/export/create, project export/import, print report). toolbox_hidden tools stay callable via the API but don't appear in the toolbox UI; beta tools render in a Beta sub-section; worker_tag routes the job to a specific Windmill worker (e.g. print).

How Tools Execute

1. Frontend calls the processes service API to start a tool
2. processes creates a job in customer.job and submits it to Windmill
3. Windmill runs the generated Python script, which imports from goatlib.tools
4. The tool class (BaseToolRunner subclass) reads input from DuckLake, processes, writes output to DuckLake
5. Job status is tracked in customer.job (pending → running → finished/failed)

Adding / Changing a Tool

1. Add or edit the tool class in goatlib/tools/<name>.py (inherit BaseToolRunner[TParams])
2. Register it in goatlib/tools/registry.py (TOOL_REGISTRY) — this is what makes it appear everywhere
3. Sync to Windmill (reads WINDMILL_URL / WINDMILL_TOKEN from the environment):

set -a && source .env && set +a
uv run python -m goatlib.tools.sync_windmill

Checking Jobs

Via Windmill MCP, or via the database (see the db skill for connection):

SELECT id, type, status, created_at, payload->>'tool_type' AS tool
FROM customer.job ORDER BY created_at DESC LIMIT 10;

Key Code Paths

• Tool registry (source of truth): packages/python/goatlib/src/goatlib/tools/registry.py
• Tool base class: packages/python/goatlib/src/goatlib/tools/base.py
• Individual tools: packages/python/goatlib/src/goatlib/tools/<name>.py
• Windmill sync: packages/python/goatlib/src/goatlib/tools/sync_windmill.py
• Code generation: packages/python/goatlib/src/goatlib/tools/codegen.py
• Processes API: apps/processes/ (OGC API Processes service)