console: chain of thought, from data the console already has

Follows the previous commit but drops everything that would have needed a
backend change. The chain is built entirely from the audit trail the console
already fetches: the REASONED rung is the employee's own reasoning fields
(attribution_reason, ai_recommendation_rationale, and the rest — already in the
data), and the DECIDED rung is the activity it committed, the state it moved the
lead to, and its confidence (ai_recommendation_confidence, also a real field on
the step). The finding stays visible above the chain.

No dependency on any endpoint change: the tool-call rung and the tbl_ai_decisions
join are gone. What remains is real, self-contained, and ships with a push.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

src/components/ChainOfThought.css

@@ -0,0 +1,59 @@
+.cot { margin-top: var(--sp-2); }
+
+/* The finding, always visible — the one sentence that answers "what did it
+   conclude" without opening anything. */
+.cot__finding {
+  margin: 0 0 var(--sp-2);
+  font-size: var(--fs-sm);
+  line-height: var(--lh-normal);
+  font-weight: var(--fw-medium);
+  color: var(--zk-ink);
+}
+
+.cot__toggle {
+  display: inline-flex;
+  align-items: center;
+  gap: var(--sp-2);
+  padding: var(--sp-1) 0;
+  border: 0;
+  background: none;
+  cursor: pointer;
+  font: inherit;
+  font-size: var(--fs-2xs);
+  font-weight: var(--fw-semi);
+  color: var(--zk-blue-dark);
+}
+.cot__brain { width: 15px; height: 15px; flex: none; }
+.cot__ct { color: var(--zk-grey); font-weight: var(--fw-normal); }
+.cot__caret { width: 11px; height: 11px; transition: transform .18s var(--ease); }
+.cot__caret.is-open { transform: rotate(90deg); }
+
+.cot__steps {
+  list-style: none;
+  margin: var(--sp-3) 0 0;
+  padding: var(--sp-3) 0 var(--sp-2);
+  border-left: 2px solid var(--zk-blue-light);
+  padding-left: var(--sp-4);
+}
+
+.cot__step { position: relative; display: grid; grid-template-columns: 82px 1fr; gap: var(--sp-3); padding: var(--sp-2) 0; }
+.cot__step::before {
+  content: ""; position: absolute; left: calc(var(--sp-4) * -1 - 6px); top: 9px;
+  width: 9px; height: 9px; border-radius: 50%; background: var(--zk-white); border: 2px solid var(--zk-blue);
+}
+
+.cot__mark {
+  font-size: var(--fs-3xs);
+  font-weight: var(--fw-semi);
+  letter-spacing: .06em;
+  text-transform: uppercase;
+  color: var(--zk-blue-dark);
+  padding-top: 1px;
+}
+
+.cot__b { font-size: var(--fs-xs); line-height: var(--lh-normal); color: var(--zk-muted); overflow-wrap: anywhere; }
+.cot__b b { color: var(--zk-ink); font-weight: var(--fw-semi); }
+
+.cot__foot { display: flex; flex-wrap: wrap; gap: 6px; margin-top: var(--sp-2); }
+.cot__conf { font-size: 11.5px; font-weight: var(--fw-semi); color: var(--zk-blue-dark); background: var(--zk-tint-blue); border: 1px solid var(--zk-blue-light); padding: 1px 9px; border-radius: var(--r-pill); }
+

src/components/ChainOfThought.jsx

@@ -0,0 +1,87 @@
+import { useState } from 'react'
+import './ChainOfThought.css'
+
+/**
+ * How an AI employee reached a decision, step by step.
+ *
+ * This is the trust surface. A person signing off on — or overriding — a
+ * machine's decision needs the answer to one question first: WHY did it do
+ * that. Before this, the reasoning existed (the employees write it as workflow
+ * fields, so it is already in the audit trail) but the console showed only the
+ * conclusion. An operator either trusted it blind or went digging. Neither is
+ * oversight.
+ *
+ * The chain reads the way the employee's own record reads: what it REASONED and
+ * what it DECIDED. It is assembled from real fields already on the step — the
+ * employee's own words for the reasoning, the activity it committed and the
+ * state it moved the lead to for the decision — never narrated after the fact.
+ * A step may carry more than one reasoning field (attribution AND eligibility,
+ * say); each is its own rung.
+ *
+ * The finding — the first sentence, since the employees write the conclusion
+ * first — is lifted out and stays visible, so the "why" can be read without
+ * opening the chain.
+ */
+function findingOf(text) {
+  const m = String(text).match(/^(.{24,200}?[.!?])(\s|$)/)
+  return m ? m[1].trim() : null
+}
+
+export default function ChainOfThought({ reasoning, decided, confidence }) {
+  const [open, setOpen] = useState(false)
+
+  const primary = reasoning.length ? reasoning[0][1] : ''
+  const finding = findingOf(primary)
+
+  const steps = reasoning.length + 1 // each reasoning rung, plus Decided
+
+  return (
+    <div className="cot">
+      {finding ? <p className="cot__finding">{finding}</p> : null}
+
+      <button
+        type="button"
+        className="cot__toggle"
+        aria-expanded={open}
+        onClick={() => setOpen((v) => !v)}
+      >
+        <svg className="cot__brain" viewBox="0 0 16 16" aria-hidden="true">
+          <path d="M6 2.5a2 2 0 0 0-2 2 2 2 0 0 0-1 3.7A2 2 0 0 0 4 11.5a2 2 0 0 0 2 2M10 2.5a2 2 0 0 1 2 2 2 2 0 0 1 1 3.7 2 2 0 0 1-1 3.3 2 2 0 0 1-2 2M8 3v10"
+                fill="none" stroke="currentColor" strokeWidth="1.2" strokeLinecap="round" />
+        </svg>
+        Chain of thought
+        <span className="cot__ct">· {steps} step{steps === 1 ? '' : 's'}</span>
+        <svg className={'cot__caret' + (open ? ' is-open' : '')} viewBox="0 0 12 12" aria-hidden="true">
+          <path d="M4 2.5 8 6l-4 3.5" fill="none" stroke="currentColor" strokeWidth="1.6"
+                strokeLinecap="round" strokeLinejoin="round" />
+        </svg>
+      </button>
+
+      {open ? (
+        <ol className="cot__steps">
+          {reasoning.map(([label, text], i) => (
+            <li className="cot__step" key={label}>
+              <span className="cot__mark">{i === 0 ? 'Reasoned' : label}</span>
+              <div className="cot__b">{text}</div>
+            </li>
+          ))}
+
+          <li className="cot__step">
+            <span className="cot__mark">Decided</span>
+            <div className="cot__b">
+              <b>{decided.what}</b>
+              {decided.stage ? <> — moved to <b>{decided.stage}</b></> : null}
+              {confidence != null ? (
+                <div className="cot__foot">
+                  <span className="cot__conf">
+                    {Math.round(confidence * (confidence <= 1 ? 100 : 1))}% confidence
+                  </span>
+                </div>
+              ) : null}
+            </div>
+          </li>
+        </ol>
+      ) : null}
+    </div>
+  )
+}

src/components/Timeline.jsx

@@ -2,6 +2,7 @@ import { useState } from 'react'
 import { useZino } from '../api/provider.jsx'
 import AgentChip from './AgentChip.jsx'
 import ClampText from './ClampText.jsx'
+import ChainOfThought from './ChainOfThought.jsx'
 import { AGENTS } from '../api/agents.js'
 import { APP_ID, STAGES, baseFieldId } from '../api/config.js'
 import './Timeline.css'
@@ -23,23 +24,34 @@ import './Timeline.css'
  * that did appear was an accident (a DATA_UPDATE row happens to write the
  * unsuffixed key).
  */
-const NARRATIVE = [
+/* AN AI STEP'S REASONING, in the order it is worth reading. These become the
+   "Reasoned" rung of the chain of thought — the employee's own words for why
+   it did what it did — rather than loose quote blocks. The first present one
+   is the finding shown without opening the chain. */
+const REASONING = [
   ['attribution_reason', 'Attribution'],
   ['eligibility_reason', 'Eligibility'],
-  ['dedupe_match_ref', 'Duplicate of'],
-  ['contact_notes', 'Call'],
-  ['ai_recommendation_rationale', 'Recommendation'],
-  ['quoted_breakup', 'How the premium was reached'],
+  ['ai_recommendation_rationale', 'Cover advice'],
   ['kyc_mismatch_notes', 'KYC'],
   ['referral_analysis', 'Referral analysis'],
-  ['uw_decision_notes', 'Underwriting decision'],
+  ['uw_decision_notes', 'Underwriting'],
+  ['contact_notes', 'Call'],
   ['documents_notes', 'Documents'],
-  ['customer_reply', 'The customer said'],
-  ['customer_answer', 'We replied'],
+  ['quoted_breakup', 'How the premium was reached'],
   ['lost_reason', 'Why it was dropped'],
   ['resume_note', 'Why now'],
 ]
 
+/* CONVERSATION lines stay as plain quotes — they are what was said to and by
+   the customer, not the machine's reasoning, and belong beside the thread. */
+const CONVERSATION = [
+  ['customer_reply', 'The customer said'],
+  ['customer_answer', 'We replied'],
+  ['dedupe_match_ref', 'Duplicate of'],
+]
+
+const NARRATIVE = [...REASONING, ...CONVERSATION]
+
 const MONEY = new Set(['quoted_premium', 'commission_amount', 'sme_value_at_risk', 'motor_idv'])
 
 /**
@@ -261,9 +273,22 @@ export default function Timeline({ rows, onOpenAgent, onOpenChat, onOpenCall })
       stage: moved ? stage : null,
       when: when(r.created_at),
       docs,
-      narrative: NARRATIVE
+      // The reasoning rungs of the chain of thought — the employee's own text.
+      reasoning: REASONING
         .map(([k, label]) => [label, byBase.get(k)?.value])
         .filter(([, v]) => v !== undefined && v !== null && typeof v !== 'object' && String(v).trim() !== ''),
+      // Conversation lines stay as plain quotes.
+      conversation: CONVERSATION
+        .map(([k, label]) => [label, byBase.get(k)?.value])
+        .filter(([, v]) => v !== undefined && v !== null && typeof v !== 'object' && String(v).trim() !== ''),
+      // The decision's confidence, when the step recorded it — ai_recommendation_confidence
+      // is a real field the advice step writes into the audit data, so it needs
+      // no backend change to reach here.
+      confidence: (() => {
+        const c = byBase.get('ai_recommendation_confidence')?.value
+        const n = c == null ? null : Number(c)
+        return Number.isFinite(n) ? n : null
+      })(),
       figures: [...byBase]
         .filter(([base, f]) => MONEY.has(base) && f.value)
         .map(([base, f]) => [base.replace(/_/g, ' '), '₹' + Number(f.value).toLocaleString('en-IN')]),
@@ -315,7 +340,7 @@ export default function Timeline({ rows, onOpenAgent, onOpenChat, onOpenCall })
       last.when = it.when
       // Keep the newest line as the preview — an operator scanning the trail
       // wants where the conversation GOT to, not where it started.
-      if (it.narrative.length) last.narrative = it.narrative
+      if (it.conversation.length) last.conversation = it.conversation
       last.docs = last.docs.concat(it.docs)
       continue
     }
@@ -407,7 +432,33 @@ export default function Timeline({ rows, onOpenAgent, onOpenChat, onOpenCall })
                 </div>
               ) : null}
 
-              {it.narrative.map(([label, v]) => (
+              {/* THE CHAIN OF THOUGHT. For an AI step, the reasoning is not a
+                  loose quote — it is how the employee reached the decision, so
+                  it renders as the chain: what it checked, what it reasoned,
+                  what it decided. This is the answer to "why did it do that",
+                  which is the first thing a person needs before trusting or
+                  overriding a machine. */}
+              {it.kind === 'ai' && it.reasoning.length ? (
+                <ChainOfThought
+                  reasoning={it.reasoning}
+                  confidence={it.confidence}
+                  decided={{ what: it.what, stage: it.stage ? it.stage.name : null }}
+                />
+              ) : null}
+
+              {/* A human step's reason, and the AI step's reasoning when it is
+                  not the story's actor (rare), stay as a plain quote. */}
+              {it.kind !== 'ai'
+                ? it.reasoning.map(([label, v]) => (
+                    <div className="tl__say" key={label}>
+                      <span className="tl__saylabel">{label}</span>
+                      <ClampText text={String(v)} title={`${label} — ${it.what}`} lines={2} threshold={120} />
+                    </div>
+                  ))
+                : null}
+
+              {/* What was said to and by the customer — always a plain quote. */}
+              {it.conversation.map(([label, v]) => (
                 <div className="tl__say" key={label}>
                   <span className="tl__saylabel">{label}</span>
                   <ClampText text={String(v)} title={`${label} — ${it.what}`} lines={2} threshold={120} />