Sentiment Priority Scorer

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name: sentiment-priority-scorer description: "Score normalized real-estate leads using sentiment, urgency, intent, recency, and record type to produce deterministic priority rankings and P1-P3 buckets. Use when users ask to prioritize hot leads, rank callback queue, or triage follow-ups without performing writes or outbound sends. Recommended chain: india-location-normalizer then sentiment-priority-scorer then summary-generator and action-suggester."

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Sentiment Priority Scorer

Produce deterministic priority scores for leads without mutating any state.

Quick Triggers

Rank leads by urgency and tone for callback priority.

Classify leads into P1/P2/P3 queue.

Score follow-up priority from normalized lead records.

Recommended Chain

india-location-normalizer -> sentiment-priority-scorer -> summary-generator

Execute Workflow

1. Accept input from Supervisor containing normalized leads. 2. Validate input with references/sentiment-priority-input.schema.json. 3. Score each lead with: - sentiment_score in range [-1, 1] - intent_score in range [0, 1] - recency_score in range [0, 1] - mapped urgency_score from lead urgency (high=1.0, medium=0.6, low=0.3) 4. Use record_type to avoid over-prioritizing generic bulk inventory: - buyer_requirement: apply +0.10 intent lift (hard demand signal) - inventory_listing: no lift unless high-action cues are present 5. Boost intent_score when high-action cues exist in listing text: - immediately, keys at office, one day notice, possession, inspection any time 6. Compute priority_score on a 0-100 scale: - priority_score = 100 * (0.40*urgency_score + 0.30*intent_score + 0.20*recency_score + 0.10*sentiment_risk) - sentiment_risk = max(0, -sentiment_score) 7. Assign buckets: - P1 for priority_score >= 75 - P2 for priority_score >= 50 and < 75 - P3 for < 50 8. Produce plain-language evidence tokens that explain the score, including record-type evidence. 9. Validate output with references/sentiment-priority-output.schema.json.

Enforce Boundaries

Never write to Google Sheets, databases, or files.

Never send messages or trigger outbound channels.

Never create reminders or execute actions.

Never bypass Supervisor routing or approvals.

Never replace upstream urgency; only derive scoring fields.

Handle Errors

1. Reject schema-invalid inputs. 2. Return field-level reasons when scoring cannot be computed. 3. Fail closed if required scoring features are missing.