/field-service-objective-designer-configure

name: field-service-objective-designer-configure
description: "Designs service objectives for a Salesforce Field Service scheduling policy via a structured trade-off interview. Guides the user through objective selection and derives weights by establishing crossover equivalences against Minimize Travel (the anchor). Produces a finalized weight table with penalty-rate interpretation and a plain-English policy summary. Use this skill when a user wants to design or weight Field Service scheduling service objectives; called after work rule design and delegates to sfs-sobject-create for record creation."
user-invocable: false
owning_team: sfs-setup-experience
metadata:
  version: "1.0"
  domains: ["Field Service"]
  cliTools:
    - tool: ["sf"]
      semver: ">=2.0.0"

Managing Sfs Service Objective Designer

When to Use This Skill

Designs service objectives for a Salesforce Field Service scheduling policy via a structured trade-off interview. Guides the user through objective selection and derives weights by establishing crossover equivalences against Minimize Travel (the anchor). Produces a finalized weight table with penalty-rate interpretation and a plain-English policy summary. Called after work rule design; delegates to sfs-sobject-create for record creation.

Workflow

Salesforce Field Service – Service Objective Designer

**Designs the service objectives for a scheduling policy.** This skill collects the objective selection and derives each objective's weight through a structured trade-off interview — one question at a time — and emits a `serviceObjectives[]` block as output. It does not create any Salesforce records. When complete, delegates to `sfs-sobject-create`.

**Interview phases:** Scheduling Policy → Work Rules → **Service Objectives** (this skill) → Record Creation

This skill covers the service objective phase only. The `policy` block (from `sfs-scheduling-policy-designer`) and the `workRules[]` block (from `sfs-work-rule-designer`) arrive as context; this skill adds `serviceObjectives[]` and hands the complete design to `sfs-sobject-create`.

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Background: How SFS Scoring Works

The optimizer assigns penalty points to each candidate schedule. Lower total penalty = better schedule. Each service objective contributes penalty points based on its weight and its own scale (the worst-case scenario for that objective).

**Minimize Travel weight is the anchor** — its value is set at 1000 and all other weights are derived relative to it. The general formula, common to every objective (stated once — not re-derived per objective):

penaltyPerViolation = max( 1, roundingFn( (1000 × weight) / scale ) ) × finalMultiplier
total_penalty       = ceil( violations / granularity ) × penaltyPerViolation

Two consequences of the shared ×1000 internal multiplier:

• It cancels out of every derivation between two objectives — which is why the continuous approximations used in the interview stay valid and every "derive weight_X from weight_Y" formula is clean of any ×1000 term. Where the rounding function isn't exact for integer weights (ASAP's round, Skill Level/Preference's roundInt), small drift is possible — flagged per objective below.
• The `max(1, …)` floor guarantees every included objective has some effect even at a very low weight.

**One exception:** Same Site's final multiplier (×0.01) nets to an effective ×10, not ×1000 — the one place the "just divide by the other objective's rate" shortcut needs adjustment.

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Penalty Formulas by Objective

Use these to show math and back-calculate weights. General mechanics (×1000, floor, why derivations stay valid) are above and not repeated.

**Minimize Travel (anchor)** — Scale 120 min (2 hr = default `MaxGrade__c`), round5, ×1/60 (per-minute → per-second). `penaltyPerViolation_travel = max(1, round5(1000×weight_travel/120)) × (1/60)`. At weight 1000 → 8333.33333 → 138.88889 pts/sec (whole-second granularity). Continuous: `travel_penalty(X_min) ≈ X × weight_travel/120` — ≈8.333 pts/min at 1000. *Precision:* Travel is per-second; Overtime (same scale) is per-minute — a 61-sec trip costs more than a 60-sec one. Floor binds only below weight ≈0.12.

**Same Site** — Scale 1 (binary), round5, ×0.01 → **effective ×10, the exception**. `penaltyPerViolation_same_site = max(1, round5(1000×weight_same_site)) × 0.01`. At weight 50 → 500 pts/violation. *Precision:* round5 exact for integer weights. Flat per-event regardless of time. Effective multiplier is ×10, not ×1000.

**Minimize Overtime** — **Identical mechanics to Minimize Travel** (scale 120, round5, weight 1000 → 8333.33333) **except two differences:** final multiplier is ×1.0 not ×1/60, so the rate is per-**minute** (8333.33333 pts/min); and penalty groups into whole minutes — `overtime_penalty(X_sec) = ceil(X_sec/60) × penaltyPerViolation` — so a 61-sec block costs the same as a 120-sec one. `penaltyPerViolation_overtime = max(1, round5(1000×weight_overtime/120)) × 1.0`. Continuous: `≈ Z × weight_overtime/120`; comparable to Travel. *Precision:* Floor binds below weight ≈0.12.

**Preferred Resource** — Scale 1 (binary), roundInt, ×1.0. `penaltyPerViolation_preferred = max(1, roundInt(100 × 10.0 × weight_preferred)) × 1.0` (100×10.0 = 1000, just decomposed). At weight 375 → 375,000 pts/violation. Derivation: `weight_preferred = T_equiv × (weight_travel/120)` — with weight_travel 1000: `= T_equiv × 8.333`. *Precision:* Zero rounding error for integer weights (exact form `X_violations × 1000 × weight_preferred`). Floor only below weight 0.001.

**Resource Priority** — Scale 10 (priority 0–10; 0 = best, 10 = lowest), no rounding (raw decimal). `penaltyPerViolation_resource_priority = max(1, (weight_resource_priority/10.0) × 1000)`. At weight 1875 → 187,500 pts/priority point. Total for priority P: `P × penaltyPerViolation`. P=0 → 0; P=10 → max. *Precision:* Full float, no rounding. Linear — priority 5 = 50% of max.

**Skill Level** — Scale 10 (10-point skill