data-cleanup

Data Cleanup

Two jobs in one skill for the recurring "my CRM is messy" pain (Sidekick's #1 negative-sentiment JTBD):

• Health check (report-only): a scored structural audit of a CRM board — missing-data patterns, stalled groups, abandoned columns, automation gaps, and a 0–100 data-quality score — published as a diagnosis doc. No writes.
• Cleanup (fix): audit the board for data gaps, let the user pick which to fix, then run a bounded, idempotent write loop.

Flow (report): Trigger → Gather → Score (5 strands) → Publish diagnosis doc → offer to fix. Flow (fix): Trigger → Audit → User picks gaps → Plan writes → Execute (bounded, idempotent) → Summary.

Input

• Optional: board name/ID via argument.
• Optional: pre-declared mode (Default / Silent / Proactive).

Output

• α (default): Bounded write loop on the chosen board. Normalizes phone/country/email; can also batch-set owner / source / last-touch / stage when the user explicitly picks those gap types and signals are clean. A Hygiene fix — <Mon DD> doc lists every change with Generated by Claude footer + <!-- claude-skill-id: data-cleanup -->.
• β (opt-in): A "before/after" snapshot doc (preserves the prior state for ~30 days, in case a pass over-corrected). User is asked at Step 4.
• Proactive extension: Out of scope — data-cleanup is already a write skill; proactive doesn't change its behavior. Default mode + batched confirm is the only write surface.

Knowledge

• Gap taxonomy + audit rules (§ Step 3).
• Normalization recipes (§ Step 5).
• Shared artifact conventions (§ Shared patterns).

Tools (MCP)

• get_user_context, list_workspaces, search, get_board_info, get_column_type_info, get_board_items_page, board_insights — Gather.
• list_users_and_teams — enumerate users for bulk-assign owner step.
• change_item_column_values — the core write. Loop with bounded concurrency.
• create_doc / create_update — publish summary + before/after snapshot.
• all_monday_api — escape hatch for column types not exposed by change_item_column_values. For country columns, use: change_multiple_column_values with column_values: {"<country_col_id>": {"countryCode": "<ISO2>", "countryName": "<name>"}}. Do not freeform the mutation type — only this shape is supported for country columns.