lda-wf/docs/historical/superpowers/plans/2026-05-17-reducer-source-inventory.md

Reducer Source Inventory Implementation Plan

For agentic workers: REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (- [ ]) syntax for tracking.

Goal: Represent reducers as first-class source-owned capabilities and expose the built-in reducer catalog through existing source inventory.

Architecture: Add a small immutable ReducerSpec model in wf_core, keep runtime reducer execution where it is, and extend wf_mcp capability buckets with reducer ownership metadata. Register the three built-in reducer specs under wf.std so inventory becomes honest without adding reducer-authoring UX yet.

Tech Stack: Python, dataclasses/Pydantic, pytest, existing capability source inventory.

---

File Structure

• Create src/wf_core/models/reducers.py
  • reducer capability metadata
• Modify src/wf_core/models/__init__.py and src/wf_core/__init__.py
  • export ReducerSpec
• Modify src/wf_mcp/broker/service/capability_sources.py
  • add reducer bucket, counts, and inventory listing
• Modify src/wf_mcp/broker/service/builtins.py
  • define/register built-in reducer specs under wf.std
• Modify tests/wf_mcp/test_service.py
  • assert reducer inventory
• Update docs/wf_mcp_capability_sources.md
  • document reducers under wf.std
• Update docs/workflow_capabilities.md
  • name reducers as workflow-facing capabilities

Tasks

Task 1: Pin Inventory Behavior

• Add failing tests proving:
  • wf.std owns built-in reducers
  • source status exposes reducer_count
  • source inventory exposes reducer names
• Run focused service tests and confirm failure before implementation.

Task 2: Add ReducerSpec and Source Buckets

• Add ReducerSpec with name, description, and optional value-shape notes.
• Export ReducerSpec from core.
• Extend CapabilityBuckets, as_status(), and as_inventory() with reducers.
• Register wf.std.replace, wf.std.append, and wf.std.merge_object in built-ins.
• Run focused service tests and confirm they pass.

Task 3: Update Docs

• Add reducers to the source vocabulary docs.
• Clarify that reducers are selected from sources; LLMs are not expected to author reducer code.

Task 4: Verify

• Run uv run --with pytest pytest tests/wf_mcp -q
• Run uv run --with pytest pytest -q
• Run uv run basedpyright --level error

Non-Goals

• reducer decorators
• reducer runtime dependency resolution from external sources
• reducer MCP tools
• non-built-in reducer libraries