data-cleanup

name	data-cleanup
description	Check your CRM board's health and clean up messy data — run a scored health check (missing fields, stalled deals, abandoned columns, automation gaps) as a report, or fix data in bulk (phone formats, missing emails, country codes, unowned deals, stale dates). Use when someone says "clean my CRM", "fix my data", "normalize my phone numbers", "fill in missing owners", "run a board health check", "audit my CRM board", "what's broken in my CRM", "what are the data gaps on my board", "board is messy", or "clean up before my kickoff call".
argument-hint	[optional: board name or ID]
user-invocable	true
allowed-tools	["Read","AskUserQuestion","mcp__monday__get_user_context","mcp__monday__list_workspaces","mcp__monday__search","mcp__monday__get_board_info","mcp__monday__get_column_type_info","mcp__monday__get_board_items_page","mcp__monday__board_insights","mcp__monday__get_board_activity","mcp__monday__change_item_column_values","mcp__monday__create_doc","mcp__monday__create_update","mcp__monday__create_notification","mcp__monday__list_users_and_teams","mcp__monday__all_monday_api"]

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.

Cross-skill handoffs

• From daily-briefing: if the daily brief flags >N hygiene issues or >30% unowned deals, suggest this skill (health check first, then fix).
• From forecast / workspace-builder: if forecast-critical fields are missing or a freshly built board needs a fill-rate audit, route here.
• To daily-briefing / forecast: clean data feeds them — point the user there once cleanup is done.

---

Step 0: Connector check

Goal: Fail fast if the user has no monday MCP connection — no partial writes, no guessing.

1. Try mcp__monday__get_user_context.
2. If the tool is missing, returns an auth-style error, or the user has no accessible workspace: print "I don't see the monday connector active on this session. Install it from https://monday.com/mcp, then run this skill again." and stop.
3. If it works, cache user.id + user.name for artifact metadata.

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Step 1: Detect mode

• Default — confirm before each batch (not each item) of writes.
• Silent — skip batch confirms; still publishes the summary doc.
• Proactive — same as Default for this skill (proactive doesn't make sense — every write is intentional). If user pre-declared Proactive, treat it as Default and note in chat.

Hard safety rail regardless of mode: no deletes, no amount-column writes, no cross-workspace moves, no normalization on columns the user didn't pick. Stage / owner / source / last-touch edits ARE allowed when the user explicitly selected that gap type at Step 4 — data-cleanup is the canonical place for board-wide column rewrites that other skills point users at.

Also detect report vs. fix intent:

• Report ("health check", "audit", "what's broken", "what are the data gaps", "board is messy") → run Step 2.5: Health-check report (report-only), publish the scored diagnosis doc, then offer to proceed to fixes.
• Fix ("clean", "fix", "normalize", "fill in") → skip to Step 3.
• Ambiguous → ask once: "Want a read-only health check (scored report, no changes) or to clean up the data now?"

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Step 2: Resolve board

Goal: Land on a single boardId before reading any data.

1. If the user passed a board via argument: numeric → use as boardId directly; string → mcp__monday__search with searchType: "BOARD". One match → use it; multiple → AskUserQuestion.
2. If no argument: get_user_context → scan relevantBoards + favorites for names matching deals|opportunities|pipeline|leads|sales|contacts|accounts. One candidate → use it; multiple → AskUserQuestion; zero → list_workspaces → search. Still zero → stop with "I don't see a CRM-shaped board in your workspaces. Tell me the board name or ID, or run /monday-crm:workspace-builder to create one."

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Step 2.5: Health-check report (report-only path)

Goal: Produce a scored structural audit as a doc — no writes. Run only when the user asked for a report/health check (see Step 1 intent). Otherwise skip to Step 3.

Pull board schema (get_board_info, get_column_type_info), items (get_board_items_page, up to 2K most-recent), aggregate stats (board_insights — known ~9% baseline error rate; on failure skip that strand and note it), and activity (get_board_activity, or derive staleness from item updated_at). Then score five strands:

1. Missing data — required fields (stage, owner, value, close_date) blank on >25% of items; compute fill-rate per column.
2. Stalled groups — groups with no item updates in >30 days.
3. Column drift — columns populated on <5% of items over 90 days (likely abandoned → suggest archive).
4. Automation gaps — stage-based automations absent on deal boards (probe via all_monday_api; if scope unavailable, skip with note).
5. Structure — duplicate columns, no groups, missing required column type.

Scoring (each strand 0–100, floor 0): Missing data 100 − (15·P0 + 8·P1 + 3·P2) · Stalled 100 − 15/group · Drift 100 − 8/column · Automations 100 − 20/missing stage automation · Structure 100 − 10/issue. Overall = weighted avg: Missing 40% + Stalled 20% + Drift 15% + Automations 15% + Structure 10%. Severity: P0 = fill-rate <50% on required fields, stall >90d, or no stage automation (blocks forecast/reporting). P1 = fill-rate 50–75%, stall 30–90d, column <5% populated. P2 = structural/minor.

Publish: create_doc titled Board Health Check — <board> — <Mon DD>, body carries Generated by Claude · <ISO> + <!-- claude-skill-id: data-cleanup -->. Sections: overall score + 5-strand breakdown, P0 fixes ([P0] <issue> → <fix>), P1/P2 batched, automation recommendations, column-archive list. Healthy-board shortcut: score ≥90 and zero P0/P1 → skip the doc, print the score + inline P2 notes.

Then offer to fix: "Want me to fix the fixable gaps now? I can normalize phone/email/country and bulk-set owner/source/stage within a scope you pick." → yes routes to Step 3; no stops here. Report path writes nothing.

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Step 3: Audit — surface the gaps (Gather + Synthesize)

Goal: Compute a gap report grouped by fix-type, with a concrete count per type.

Pull all items via get_board_items_page (paginated up to 5000, then sample with disclosure). For each item, check:

Gap type	Audit rule	Fixable here?
Missing email	email column empty AND contact name present AND company resolvable (see note below)	✅ (heuristic guess from company domain — flagged with Source = guessed)
Missing phone	phone column empty	❌ (no source — flag only)
Phone format	Phone present but no country code, or contains letters / >2 separators	✅ (E.164 normalization)
Country code missing	country column empty AND phone has parseable country code OR email domain has CCTLD	✅
Email case	Mixed-case ([e-mail])	✅ (lowercase)
Stale last-touch	date last-touch >90d AND stage active	✅ (set to "today" only if user picks; never overwrites a more-recent date)
Owner missing	people owner empty AND stage active	✅ (bulk-assign within a user-picked group/scope)
Stage drift	items in non-canonical groups; user explicitly wants normalization	✅ (bulk-set within user-picked scope)
Amount missing	numbers value empty AND stage past "qualifying"	❌ (flag only — forecast integrity rail)
Source missing	status source column empty	✅ (bulk-set within user-picked scope)

"Company resolvable" definition for email guessing: look for (a) a text or email column containing a domain (@ or .), (b) a board_relation column linking to an accounts board, or (c) an item name matching First Last @ CompanyName. If none found, mark the item as not guessable.

Resolve columns by type, not English name (same rule as daily-briefing). Skip gap types where the matching column doesn't exist.

Produce the audit summary in chat:

## Audit — <board name>

**Items scanned:** N
**Gaps found:**
- ✅ Fixable (column normalization): <N> phone formats · <N> mixed-case emails · <N> missing country codes · <N> guessable missing emails
- ✅ Fixable (bulk-set within picked scope): <N> missing owners · <N> stale last-touch · <N> missing sources · <N> stage drift
- ⚠️ Flag-only: <N> missing phones (no source) · <N> missing amounts (forecast integrity rail)

Pick which fixable gaps to run, or "all". Flag-only items list in the summary doc — no writes.

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Step 4: User picks (Synthesize)

First, ask whether to create a before/after snapshot: "Want a snapshot doc so you can see exactly what changed and roll back individual cells if something looks off? (yes / no)"

Then AskUserQuestion, multiSelect:

• "Phone formats (N items)"
• "Mixed-case emails (N items)"
• "Country codes from phone/email (N items)"
• "Guess missing emails from company domain (N items) — heuristic, may miss"
• "Bulk-assign owner (N items) — requires picking a scope and a target owner"
• "Backfill stale last-touch (N items) — will only fill empty or older-than-90d cells"
• "Bulk-set source (N items) — requires picking a scope and a source value"
• "Normalize stage drift (N items) — requires picking a scope and target stage"
• "All column-normalization fixes" (the first four — bulk-set ones still need scope)

Scope picker for bulk-set options: if the user picked multiple bulk-set options (owner / source / stage / last-touch), ask once: "Should the same scope (group / filter) apply to all of them, or do you want to set each separately?" One question beats four. If "same for all" → ask scope once and apply it across all bulk-set options. If "separately" → run a scope sub-prompt per option.

For bulk-set options, use list_users_and_teams to present available owners/teams when the target owner needs to be selected.

If user picks "Guess missing emails", surface a strong warning: "Email guessing uses a <first>.<last>@<companydomain> pattern. Accuracy varies widely — works best for B2B companies with standard email formats, unreliable for personal domains or non-Western name conventions. Only recommended for Leads boards where invalid sends are tolerable. Continue?"

Hard rule: no fix runs without an explicit Step 4 selection (and a scope-picker confirm for bulk-set options). Empty selection → stop with summary-only.

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Step 5: Plan + execute (Publish)

Goal: Bounded, idempotent loop. Every write is reversible.

For each picked gap type, build a write plan: list of (itemId, columnId, oldValue, newValue, reason).

Normalization recipes

• Phone format → E.164:
  • Strip non-digit/+ characters.
  • If no leading + AND country column is populated → prepend dial code per country.
  • If no leading + AND country empty AND phone starts with a known country prefix (e.g., 1 for US, 44 for UK) → prepend +.
  • Edge case: phone is too short (<7 digits) or too long (>15 digits) → skip with reason "unparseable".
• Email lowercase: value.toLowerCase(). Only write if changed.
• Country code from phone: parse leading dial code → ISO-2 country code → write to country column using all_monday_api with {"countryCode": "<ISO2>", "countryName": "<name>"} shape.
• Country code from email CCTLD: if email ends in .uk / .de / .fr etc. and country empty → infer.
• Email guess: for items with name + resolvable company domain, try <firstname>.<lastname>@<domain> lowercase. Add a Source = guessed status flag on the item so the user can filter and verify later. If a source/status column is missing, prompt the user once to add one — never write the email without a verifiability flag.
• Bulk-set owner / source / stage: within the user-confirmed scope (group / status filter from Step 4), apply the chosen target value via change_item_column_values. Never extend beyond the picked scope.
• Backfill stale last-touch: set to today's date only on items where last-touch is (a) empty, or (b) older than 90 days AND user explicitly picked the "stale last-touch" gap type. Never overwrite a more-recent date.

Bounded execution

1. Cap total writes at 500 per run. Above that, prompt: " writes planned, capped at 500 per run. Run first 500 now and re-trigger for the rest, or narrow your selection?"
2. Execute via change_item_column_values, batched by item (one call per item updates multiple columns at once). Concurrency: 5 in flight max to avoid rate limits.
3. Confirm before write (Default mode) — single batched plan:
   • "Plan: phone normalizations · email lowercase · country fills · owner assignments (scope: ) · source backfills (scope: ) · stale-last-touch fills · stage drift fixes (scope: → ). Proceed? (yes / show 3 examples per fix-type / no)."
4. After each batch of 50 writes, print progress: Updated 50/500 cells. Continuing...

Idempotency

Compute oldValue == newValue per cell — never write a no-op (avoids audit-log noise).

Failure handling

• 429 rate limit: backoff 3x (1s, 2s, 4s). On third fail, halt the loop and emit a partial summary with "/ done; failed; re-run to continue."
• Per-item permission error: skip that item, log to summary, continue.
• Per-column write error (e.g., column type changed mid-run): skip that column on that item, log, continue.
• User halts mid-run: keep writes done so far, emit partial summary doc. Print the last item ID written so the user can pick up from there.

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Step 6: Publish summary doc (Publish)

create_doc (idempotent — search same-day docs by title + skill-id comment, update in place if found), title Hygiene fix — <Mon DD>. Body:

# Hygiene fix — <board name> · <Mon DD>

<!-- claude-skill-id: data-cleanup -->

## Writes executed (<N>)
| Item | Column | Old → New | Scope / reason |
|---|---|---|---|
| ... | ... | ... | ... |

## Skipped (<N>)
| Item | Column | Reason |
|---|---|---|

## Flag-only (no writes)
- N items missing phone (no source — manual entry required)
- N items missing amount (forecast integrity rail — review manually)

## Undo
Every write here is reversible. The "Old" column above shows the prior value. To revert: find the row in monday and copy the Old value back in manually.

---
Generated by Claude · <ISO timestamp>

Optional β: create_update on a "snapshot" item with the pre-fix state of every touched item, for 30-day rollback window. Only runs if user opted in at Step 4.

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Step 7: Close the loop