메뉴
Identifies cancelled and downgraded customers in the window, with prior MRR, current MRR, delta, and reasons pulled from Stripe cancellation_details and Postgres support_notes. Sub-step inside revenue-recovery.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Run Mimic-generated eval scenarios against a target agent skill (default `revenue-recovery`) inside this Claude Code session. Reads `.mimic/exports/mimic-scenarios.json`, sub-agents one run per scenario via the Agent tool, scores responses with hybrid (strict substring + LLM-judge-on-miss + numeric-range) checks, and prints a scored table. Use when the user says any of "run the mimic eval", "score the agent", "eval against the facts", "/mimic-eval".
Quantifies the MRR delta for a window and decomposes it into involuntary churn, voluntary churn, downgrades, refunds, and expansion offset. Sub-step inside revenue-recovery — do not invoke standalone unless the operator explicitly asks for the diagnosis only.
Pulls failed payment_intents from Stripe in the window, ranks retry candidates by success probability based on decline reason, and surfaces patterns (BIN clusters, expiry waves, single-bank declines). Sub-step inside revenue-recovery.
Compares every customer present in both Postgres and Stripe and surfaces drift — status mismatches, mrr_cents disagreements, orphans, and refunds in Stripe not reflected in payments. Sub-step inside revenue-recovery.
Use when the operator asks why MRR dropped, who's affected, or what to do about failed payments and churn. Investigates Postgres + Stripe in parallel, produces a recovery plan, and on explicit approval executes payment retries, refunds, and subscription changes against Stripe. Two-phase contract — never auto-executes writes.
Correlates affected customers (from churn-investigation, payment-failures, reconciliation) with internal risk_flags and support_notes to surface "we knew this was coming" findings. Promotes any customer with a relevant prior signal up one risk tier in the recovery plan.
| name | churn-investigation |
| description | Identifies cancelled and downgraded customers in the window, with prior MRR, current MRR, delta, and reasons pulled from Stripe cancellation_details and Postgres support_notes. Sub-step inside revenue-recovery. |
The goal is a named list of customers who left or shrank, with the human reason where one exists. Numbers are the floor; reasons are what make the recovery plan actionable.
From Postgres: subscriptions rows where canceled_at is in the window and status = 'canceled'. Join to customers for name, email, prior plan, prior mrr_cents.
In parallel from Stripe: list_subscriptions filtered by status = 'canceled' with canceled_at in the window. Capture cancellation_details.reason if present (Stripe values: cancellation_requested, payment_disputed, payment_failed, customer_service, low_quality, missing_features, switched_service, too_complex, too_expensive, unused).
Match the two lists by stripe_subscription_id. If a row exists in only one source, treat it as a reconciliation finding and pass it through — don't drop it.
From Postgres: pairs of subscriptions rows for the same customer_id where the older row was cancelled in the window and the newer row was created in the window at a lower amount_cents. The downgrade amount is prior_amount − new_amount.
If customers.plan has changed but no matching subscriptions history exists, treat it as approximate and note it.
For every cancelled or downgraded customer, query support_notes for that customer_id in the last 30 days (not just the window — the conversation that led to the cancellation usually pre-dates it). Look for:
billing (price complaints)downgrade or churn-riskQuote the most informative note verbatim — one sentence is enough. The orchestrator will surface this on the plan row.
Per row, recommend one of:
escalate_csm — voluntary cancellation, especially with a risk-signals correlation. The agent shouldn't try to win them back via tooling; a human conversation is the action.no_action — clean voluntary cancellation with cancellation_requested, no internal flags. Recovery isn't realistic.downgrade_review — for downgrades only. Note the old/new plan and amount. Operator may want to follow up with the CSM.cancel — only if the cancellation needs to be propagated to Stripe (i.e. Postgres cancelled but Stripe still active). This is a write proposal, not a recovery.All amounts in cents in structured fields. Comply with the orchestrator's "Output format conventions".
cancellations:
- customer_id: 22
name: Inkwell Co
prior_plan: enterprise
prior_mrr_cents: 49900
canceled_at: 2026-05-02
stripe_reason: customer_service
support_note (2026-04-14): "Billing dispute over April invoice — feels overcharged."
recommended_action: escalate_csm
risk_tier: high
- customer_id: 84
name: Junction Audio
prior_plan: enterprise
prior_mrr_cents: 49900
canceled_at: 2026-05-04
stripe_reason: switched_service
support_note (2026-04-15): "Considering competitor — said pricing was the deciding factor."
recommended_action: escalate_csm
risk_tier: high
downgrades:
- customer_id: 9
name: Stoneworks LLC
prior_plan: enterprise → pro
prior_mrr_cents: 49900
new_mrr_cents: 9900
delta_cents: -40000
detected_at: 2026-05-01
support_note: none in window
recommended_action: downgrade_review
risk_tier: medium
totals:
cancellation_count: 2
total_cancelled_mrr_cents: 99800
downgrade_count: 1
total_downgrade_delta_cents: -40000
*_cents fields are integer cents. $499 = 49900, not 499. The orchestrator's output-format section is authoritative.cancellation_reason as more recent. If only Postgres has it, use Postgres.payment-failures (cancelled because of repeated failed charges), let the orchestrator de-duplicate — emit them in both.cancellation_reason is null and there's no relevant support_note, emit reason: unknown. Better than guessing.