usage-metering-and-cost-attribution-pipeline-designer

name

usage-metering-and-cost-attribution-pipeline-designer

description

Design the metering → pricing → rollup → reconciliation DATA PIPELINE for a multi-tenant SaaS — a billing-safe usage-event table (metadata only, no message/file CONTENT), time-bounded rate cards, cost entries carrying idempotency keys so replays and retries never double-bill, additive rollups (an analytical projection), budgets + breach alerts, spend forecast, and reconciliation of metered totals against provider invoices. Produces the event schema, rate-card model, idempotent cost-entry contract, rollup jobs, and reconciliation loop. Use when BUILDING the metering/billing pipeline, when usage numbers do not match the invoice, or when retries double-count. Do NOT use for the unit-economics COST MODEL — what a tenant costs, whether pricing is profitable (saas-cost-architect — closest neighbor, pinned hard), AI spend guardrails/kill-switch (ai-cost-guardrail-designer), or the operational-vs-analytical split (operational-vs-analytical-splitter).

Usage Metering & Cost Attribution Pipeline Designer

Purpose

Billing-grade numbers are an engineering problem before they are a finance one: a usage event dropped or counted twice, a rate card changed without a time boundary, a rollup that is not additive, or a metered total that never gets checked against the provider's invoice — each quietly produces a number someone gets billed on. This skill designs the DATA PIPELINE that turns raw usage into trustworthy per-tenant cost: a billing-safe event table, versioned rate cards, idempotent cost entries that survive replays, additive rollups, budgets with breach alerts, a spend forecast, and a reconciliation loop against the source-of-truth invoice. The deliverable is the event schema, the rate-card model, the cost-entry + idempotency contract, the rollup jobs, and the reconciliation loop.

Standalone, not an extension of saas-cost-architect (resolved at build, D31). saas-cost-architect builds the economic MODEL — driver inventory from real bills, attribution POLICY, unit economics vs revenue, and whether a tenant is profitable; it answers "what does this cost and does pricing cover it." This skill builds the running PIPELINE that produces the numbers that model (and the invoice) depend on — event schema, idempotency keys, additive rollups, invoice reconciliation. They compose: the model decides what to attribute; the pipeline computes and reconciles it at billing grade. The overlap is the word "attribution"; the surfaces (a reasoning artifact vs an ETL/schema design) barely touch.

Use When

• Use when: BUILDING the metering/billing data pipeline — the usage-event table, rating against rate cards, cost entries, rollups, and reconciliation.
• Use when: metered usage numbers do not match the provider's invoice, or finance cannot reconcile what was billed to what was measured.
• Use when: retries, replays, or re-processing double-count usage or cost, and the pipeline needs idempotency.
• Use when: rate/price changes corrupt historical bills because rate cards have no time boundary (a price change silently re-rates last month).
• Use when: designing per-tenant budgets, breach alerts, and spend forecasts off metered data.
• Do NOT use when: the question is the COST MODEL / unit economics — what a tenant or plan actually costs, whether pricing is profitable, which tenants are underwater — that is saas-cost-architect (the closest neighbor). This skill is the pipeline that FEEDS that model, not the model.
• Do NOT use when: the subject is AI-spend guardrails specifically — per- request token caps, cost-aware rate limits, a spend kill switch — that is ai-cost-guardrail-designer; this pipeline may METER AI usage, but the budget-enforcement/kill-switch design lives there.
• Do NOT use when: the question is WHETHER analytics/rollup workloads should leave the operational store — that is operational-vs-analytical-splitter; the rollup this skill designs is an analytical projection whose placement that decision governs.

Inputs to Inspect

1. The metered activity: what generates cost or is billed (API calls, storage, seats, AI tokens, compute-minutes, third-party pass-through) — the events the pipeline must capture, and their volume.
2. The pricing model (from plan-entitlement-architect / the price book): plans, unit prices, allowances/overage, and how often prices change — the rate cards the pipeline rates against.
3. Existing metering, if any: how usage is recorded today, whether events are deduplicated, and any incident history of double-billing or unreconciled drift.
4. The provider/source-of-truth totals: the cloud/AI/third-party invoices the metered totals must reconcile against, and their granularity and lag.
5. The tenant model: how usage events carry tenant (and user/feature) context for attribution, and whether any activity is currently un-attributed.
6. Privacy constraints: what must NOT enter a usage event (message/file content, PII, prompt text) — the billing-safe boundary.

Workflow

1. Design the billing-safe usage-event table. One append-only event per metered unit: tenant_id, optional user_id/feature, metric, quantity, occurred_at, source, and a unique event_id. The discipline: METADATA ONLY — never message bodies, file contents, prompt/ response text, or PII. The event records THAT usage happened and how much, not what was in it. State the retention and that events are immutable.
2. Model rate cards with time boundaries. A rate card maps metric → price, and every card carries an effective [valid_from, valid_to) window. Rating an event uses the card in effect at the event's occurred_at, NOT the current card — so a price change never re-rates history. Version cards; never mutate a past one.
3. Design cost entries with idempotency keys. Rating produces cost entries (exact where measured, estimated where inferred, allocated where proportional — label which). Each entry carries an idempotency key derived from the event id + rate-card version, so re-running the rater, replaying events, or retrying a batch produces the SAME entry, never a duplicate. Re-processing is a normal operation; the pipeline must be safe under it.
4. Design additive rollups. Daily (and per-tenant/per-metric) rollups that SUM cost entries into aggregates. Additivity is the property that makes them safe to recompute and to combine across time — avoid rollups that can't be re-derived from the entries. State that a rollup is a projection of the entries, always reconstructable, never the source of truth. (Its analytical-store placement follows operational-vs-analytical-splitter.)
5. Design budgets, breach alerts, and forecast. Per-tenant/plan budget thresholds evaluated against rollups; alerts fired BEFORE the budget is gone (with owners); a spend forecast from the trend. Note that ENFORCING a budget (throttle/kill) — especially for AI spend — is ai-cost-guardrail-designer's job; this pipeline provides the metered signal it acts on.
6. Design the reconciliation loop — the trust anchor. Periodically compare metered totals against the provider/source-of-truth invoice per metric and tenant, compute drift, and define the tolerance beyond which the pipeline is considered broken and investigated. Metering nobody reconciles is a number nobody should bill on. Define what a discrepancy triggers (recompute, rate-card audit, missing-event hunt).
7. Design late/out-of-order and correction handling. Late-arriving events (a usage report delayed past its day) and corrections (a refund/void) as explicit additive adjustments with their own entries — never an in-place edit of a past rollup. State the close/lock policy (when a period is finalized) and how post-close corrections are booked to the next period.

Output Format

USAGE METERING & COST PIPELINE — <system/domain>
Usage-event table: <fields; METADATA ONLY (no content/PII); immutable; retention>
Rate cards:     <metric → price; [valid_from, valid_to); rate at occurred_at,
  not current; versioned, past cards immutable>
Cost entries:   <exact/estimated/allocated labeled; idempotency key =
  event_id + rate-card version; re-processing produces same entry>
Rollups:        <daily/tenant/metric SUM of entries; additive; reconstructable
  projection, not source of truth; analytical placement → operational-vs-analytical-splitter>
Budgets/alerts/forecast: <thresholds vs rollups; alert-before-gone + owners;
  forecast>; ENFORCEMENT (throttle/kill, esp. AI) → ai-cost-guardrail-designer
Reconciliation: <metered totals vs provider invoice per metric/tenant; drift +
  tolerance; discrepancy → recompute/audit/missing-event hunt>
Late/corrections: <late events + refunds/voids as additive adjustments;
  period close/lock; post-close → next period>
Boundaries:     cost MODEL / unit economics → saas-cost-architect;
  AI spend guardrails → ai-cost-guardrail-designer
Open questions / risks: <each with risk-if-wrong / who answers>

Validation Checklist

• Usage events carry metadata only — no message/file content, prompt text, or PII; events are immutable and retained.
• Rate cards are time-bounded and events are rated at their occurred_at card version; a price change never re-rates history.
• Every cost entry carries an idempotency key; re-running the rater or replaying events produces the same entry, never a duplicate.
• Rollups are additive projections of cost entries — reconstructable, and never the source of truth.
• A reconciliation loop compares metered totals to the provider invoice with a stated tolerance and a defined action on drift.
• Late/out-of-order events and corrections are additive adjustments, not in-place edits of finalized rollups; a period close/lock policy exists.
• Budget ENFORCEMENT (throttle/kill) is deferred to ai-cost-guardrail-designer; the pipeline provides the signal.
• The unit-economics/profitability question is deferred to saas-cost-architect; this skill builds the pipeline, not the model.

Gotchas

• Putting content in a usage event ("store the prompt so we can debug billing") turns the metering table into a PII/secret store with billing- grade retention — meter metadata, never payload.
• A rate card without a time boundary re-rates the past the moment you change a price: last month's invoices silently shift. Rate at occurred_at.
• No idempotency key means every retry/replay double-bills; and metering pipelines retry constantly. Idempotency is not optional here, it is the correctness property.
• Non-additive rollups (storing a computed average or a running balance you can't re-derive) can't be recomputed after a correction — keep rollups as sums of immutable entries.
• Editing a finalized rollup to "fix" a number destroys the audit trail; corrections are new, additive, signed adjustment entries.
• Metering that is never reconciled against the real invoice drifts silently until a customer disputes a bill; reconciliation is the trust anchor, not a nice-to-have.
• Late events after period close, booked into the closed period, change a finalized invoice; define the close/lock and book late items to the next period.
• Estimated and exact cost entries mixed without a label make the number un-auditable; label the basis of every entry.

Stop Conditions

• The request is really "what does a tenant/plan cost and is our pricing profitable" → route to saas-cost-architect; this skill builds the pipeline that produces the inputs to that model, not the model.
• The request is AI-spend enforcement (token caps, cost-aware rate limits, a kill switch) → route to ai-cost-guardrail-designer; this pipeline supplies the metered signal but does not design the enforcement.
• The source-of-truth invoice to reconcile against is unavailable → the pipeline can be designed, but say plainly that its numbers are unverified until reconciliation has a source; do not present unreconciled metering as billing-grade.
• Asked to run the pipeline / a re-rating job against production billing data → this skill DESIGNS; executing a re-rate or correction against live billing follows the repo's approval path (billing changes are high-blast- radius).

Supporting Files

• evals/evals.json — behavior cases: the build-the-pipeline design, the replay-idempotency edge, the reconciliation-drift case, the content-in-event refusal, and the cost-model non-trigger.
• evals/trigger-evals.json — discrimination against saas-cost-architect (THE hard-pinned seam — pipeline vs cost model), ai-cost-guardrail-designer (metering signal vs spend enforcement), and operational-vs-analytical-splitter (rollup as analytical projection).
• No references/ — the event/rate-card/idempotency/reconciliation procedure above is complete; detail lives in the produced artifacts.