Update README.md

README.md

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-# Clarity Ops — Two-Phase Medical Analytics Engine
-
-This repo implements a universal, scenario-agnostic medical analytics workflow:
-
-1) **Phase 1: Clarification Questions** (<=5, grouped by category)
-2) **Phase 2: Structured Analysis** (schema-validated, unit-checked, math-verified, policy-aligned)
-
-The engine never invents data. If inputs are missing/ambiguous, it asks for clarifications first.
-
-## Quick start
-
-1. Populate a scenario in `/packs/<scenario>/` (see `/packs/mdsi` as an example).
-2. (Optional) Put known answers to clarifications in `clarifications.json`.
-3. Run the pipeline (pseudo-call in your orchestration):
-   - `run_two_phase.run_clarityops("packs/mdsi")`
-4. Review the final JSON. It passes:
-   - JSON Schema validation
-   - Unit/range checks
-   - Math consistency
-   - Policy/constraints adherence
-5. (Optional) Compare against `/packs/<scenario>/expected.json` with the rule-based grader.
-
-## Folder overview
-- `/core`: Global medical rules (units, ranges, privacy)
-- `/prompts`: System + two-phase user template
-- `/schemas`: Output schema for Phase 2
-- `/validators`: Hard guardrails (schema/units/math/policy)
-- `/graders`: Rule-based grader for gold answers
-- `/pipeline`: Two-phase orchestration
-- `/packs/<scenario>`: Scenario Pack (inputs, constraints, schema selection, rubric, expected)
-
-## Notes
-- This repo shows reference Python code for validators and pipeline. Hook the prompts into your LLM runner of choice.
-- All numbers are examples unless your scenario pack provides them.
+# ClarityOps (LLM-Only)
+
+ClarityOps runs fully inside an LLM chat:
+1) User pastes a scenario and optionally attaches data files (CSV/XLSX/PDF).
+2) **Phase 1**: ClarityOps reads everything and asks up to 5 grouped clarification questions.
+3) User answers in the chat.
+4) **Phase 2**: ClarityOps produces a validated, structured analysis.
+
+No external code, servers, or UI — all interaction is conversational.
+
+## How to use (operator playbook)
+
+**Turn 1 (User):** Paste the scenario using `/prompts/user_scenario_template.txt`. Attach any files.
+
+**Turn 2 (Model):** ClarityOps returns **Phase 1: Clarification Questions** (≤5, grouped). It stops and waits.
+
+**Turn 3 (User):** Reply using `/prompts/answer_clarifications_template.txt`.
+
+**Turn 4 (Model):** ClarityOps returns **Phase 2: Structured Analysis** in the exact format from `/prompts/phase2_format.txt`.
+
+### Notes
+- The **system prompt** (`/prompts/system_master.txt`) enforces the two-phase behavior, numerical transparency, units, and medical guardrails.
+- The **schema** (`/schemas/phase2_output.schema.json`) is provided as a reference shape that the model mirrors in Phase 2. (The LLM follows it; there’s no external validator.)
+- The **guardrails** (`/policies/medical_guardrails.md`) define units, ranges, privacy, and recommendation style.
+