Plan Query
plan_queryIdentify which Canadian data sources answer a multi-agency question and return the topics, ordered tools, local portals, and caveats to combine them.
Instructions
Plan which sources answer a question that may span several agencies.
Use for: the first call on a substantive question ("How have rents and interest rates moved in Calgary since 2020?"). Returns the topics it touches, the tools to call for each in order, local portals for any province or city named, and caveats on combining them. Then run the steps with call_tool. lang is accepted for consistency; the plan text is English. Keywords: plan, which data source, where to find, combine sources, cross-source, question, research, Canada data. Mots-clés : planifier, quelle source de données, où trouver, combiner des sources, question, recherche, données canadiennes, statistiques.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | en | |
| question | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| places | Yes | ||
| topics | Yes | Best match first; at most 4. | |
| guidance | Yes | ||
| question | Yes | ||
| provenance | Yes | Where a result came from and how fresh/complete it is. Embedded in every module's response models (composition, not inheritance) so a tool can return `MyResult(provenance=..., ...)` without fighting Pydantic's model-inheritance rules for extra fields. | |
| fallback_steps | Yes | Only when no topic matched. |