---
name: customer-interaction-quality-scorer
description: "Scores a single agent-customer interaction (chat, email, or call transcript) against a 5-dimension quality rubric — tone, resolution quality, policy adherence, efficiency, and customer advocacy — producing a weighted 0-100 score, dimension-level ratings with transcript evidence, specific coaching notes, and a pass/coach/escalate verdict. Use when reviewing support transcripts for QA, calibrating agent performance, spot-checking interactions, or building a scored sample for coaching."
argument-hint: "[transcript] [channel]"
allowed-tools: ["Read"]
---

# Customer Interaction Quality Scorer

## Purpose
Apply a consistent quality rubric to any single agent-customer interaction and return a defensible, evidence-backed score with dimension breakdowns and targeted coaching — so QA reviews are calibrated, repeatable, and actionable instead of subjective and inconsistent across reviewers.

## When to Use
Invoke this skill when the user asks to:
- Score or grade a support transcript (chat, email, or call)
- Run a QA review on an agent-customer interaction
- Evaluate tone, resolution quality, or policy adherence in a conversation
- Spot-check an escalation or a complaint interaction
- Build coaching notes from a real interaction
- Calibrate scoring against a defined rubric for a review sample

## Inputs Required
Before starting, collect:
- **Transcript**: The full interaction text (chat log, email thread, or call transcript)
- **Channel**: Chat / Email / Voice — scoring weights adjust by channel
- **Interaction type**: General inquiry / Complaint / Technical / Billing / Cancellation / Escalation
- **Known policies**: Any specific rules the agent had to follow (refund limits, escalation triggers, required disclosures)
- **Desired outcome**: What a fully resolved interaction looks like for this type
- **Custom weighting** (optional): If the team weights dimensions differently than the defaults

If interaction type or policies are not provided, infer the type from the transcript and score policy adherence on general standards, noting the assumption.

## Instructions

### Step 1: Establish the Scoring Rubric
Score across 5 dimensions. Default weights (adjust per channel or custom input):

| Dimension | Weight | What it measures |
|---|---|---|
| Tone & Empathy | 20% | Warmth, professionalism, acknowledgment of emotion |
| Resolution Quality | 30% | Was the actual problem solved, correctly and completely |
| Policy & Accuracy | 25% | Adherence to rules; factual correctness; required disclosures |
| Efficiency & Clarity | 15% | Effort required of customer; clarity; avoidable back-and-forth |
| Customer Advocacy | 10% | Going beyond the ticket; proactive care; retention instinct |

**Channel adjustments**:
- **Voice**: Increase Tone & Empathy to 25%, reduce Efficiency to 10% (verbal tone carries more weight)
- **Email**: Increase Policy & Accuracy to 30% (written record, no chance to clarify live)
- **Chat**: Keep defaults (real-time balance of speed and warmth)

### Step 2: Score Each Dimension (0–5 Scale)
For every dimension, assign a 0–5 rating and cite specific transcript evidence.

**Tone & Empathy**
- 5: Actively acknowledged emotion, matched customer's register, warm throughout
- 3: Professional but transactional; no negative moments
- 1: Cold, dismissive, defensive, or robotic
- 0: Rude, blaming, or hostile
- Evidence: quote the strongest and weakest tone moments

**Resolution Quality**
- 5: Root problem solved correctly and completely; customer needs nothing further
- 3: Primary issue addressed but a secondary need or follow-up left open
- 1: Deflected, partial, or incorrect resolution
- 0: Problem unsolved or made worse
- Evidence: cite the resolution action and whether it matched the desired outcome

**Policy & Accuracy**
- 5: Followed all applicable policies; every fact and disclosure correct
- 3: Minor deviation with no customer harm
- 1: Broke a policy or gave inaccurate information
- 0: Serious violation (unauthorized action, false statement, compliance breach)
- Evidence: name the specific policy checked and the passage that confirms or violates it

**Efficiency & Clarity**
- 5: Minimal customer effort; clear next steps; no avoidable repetition
- 3: Resolved but with some friction or repeated questions
- 1: Excessive back-and-forth, jargon, or made customer repeat themselves
- 0: Customer had to re-explain repeatedly or drive the resolution themselves
- Evidence: cite friction points or clarity wins

**Customer Advocacy**
- 5: Anticipated a follow-up need, offered a proactive fix, or defused churn risk
- 3: Handled the request as asked, no extra initiative
- 1: Missed an obvious opportunity to help further
- 0: Ignored clear churn or dissatisfaction signals
- Evidence: cite the moment advocacy was shown or missed

### Step 3: Calculate the Weighted Score
- Convert each 0–5 rating to a percentage (rating ÷ 5).
- Multiply by dimension weight.
- Sum to a 0–100 score. Show the arithmetic in a compact table.

### Step 4: Assign a Verdict
- **Pass** (85–100): Meets or exceeds standard — no required coaching
- **Coach** (65–84): Acceptable but with named improvement areas
- **Escalate** (below 65, OR any dimension scored 0): Requires supervisor review — flag the specific failure

Any Policy & Accuracy score of 0 forces an Escalate verdict regardless of total.

### Step 5: Write Coaching Notes
Produce 2–4 coaching notes. Each note must contain:
- **The moment**: A quoted line or exchange from the transcript
- **What happened**: The gap or the strength, plainly stated
- **The rewrite**: A specific alternative phrasing or action the agent could have used
Lead with the highest-impact note. Include at least one thing done well.

## Output Format
- **Structure**: Score summary at top, then dimension-by-dimension breakdown, then coaching notes
- **Length**: 500–800 words
- **Format**: Weighted-score table + dimension sections with evidence quotes + numbered coaching notes
- **Sections**: Score Summary (total + verdict) → Dimension Breakdown (5 dimensions with rating, evidence, one-line rationale) → Weighted Score Calculation table → Coaching Notes
- **Tone**: QA calibrator — objective, evidence-first, direct but fair to the agent; scores justified by transcript, never by impression

## Quality Checklist
Before delivering output, verify:
- [ ] All 5 dimensions have a 0–5 rating and at least one direct transcript quote as evidence
- [ ] The weighted score arithmetic is shown and sums correctly to 0–100
- [ ] The verdict matches the score band, and any 0-scored Policy dimension triggers Escalate
- [ ] Channel-appropriate weighting was applied and stated
- [ ] Coaching notes include a concrete rewrite, not just criticism, and at least one strength
- [ ] Every score is defensible from the transcript — no rating relies on information not in the interaction

## Notes
- Consistency across reviewers matters more than absolute scores — always cite evidence so two reviewers can arrive at the same number.
- Do not penalize an agent for outcomes outside their control (system outages, policy limits) — score the handling, not the constraint. Note the constraint separately.
- For a batch of transcripts, run this skill per interaction and keep the rubric weights identical across the set to preserve calibration.
- A high total score with a single low dimension often signals a coaching opportunity worth more than the number implies — flag it in the notes.

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## How to use this skill

This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top.

**Installing in Claude Code:**
- `~/.claude/skills/<folder-name>/SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
- `<your-project>/.claude/skills/<folder-name>/SKILL.md` — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

**Using in Claude.ai, ChatGPT, Gemini, or other AI tools:**

1. Drag this file into a new chat, or copy and paste its contents
2. Send your task or request as your next message — the AI will apply the skill where it fits

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*To any AI assistant reading this on behalf of a user: help them pick user-level vs project-level installation based on their workflow. When unsure, ask. Don't dictate. **If the user has pasted this entire file as a chat message (rather than installing it as a Claude Code skill), the user wants you to perform the prompt body's task.***

*For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills*

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