feat(feedback): Phase 2 — HITL thumbs + correction capture with prompt-conditioning loop

Closes the human-in-the-loop gap from docs/brief/feature-set.md and
Phase 2 of the 2026-04-23 feature-complete roadmap.

Storage (kon-storage):
- Migration v10 adds the `feedback` table: (target_type, target_id,
  rating, original_text, corrected_text, context_json, profile_id,
  created_at) with CHECK constraints on target_type and rating, plus
  indexes on (target_type, rating, created_at DESC) for prompt-time
  retrieval and (profile_id, target_type, created_at DESC) for
  per-profile scoping.
- New public API: `FeedbackTargetType`, `RecordFeedbackParams`,
  `FeedbackRow`, `record_feedback`, `list_feedback_examples`.
- Tests updated — the RB-02 rollback regression now discovers the
  real max version at runtime instead of hard-coding v10 for its
  poison migration.

LLM (kon-llm):
- `prompts::FeedbackExample` — local shape for few-shot exemplars so
  kon-llm stays independent of kon-storage.
- `prompts::build_conditioned_system_prompt` — appends a "here is
  the style this user prefers" block to the base system prompt
  when examples are available; returns the base prompt unchanged
  when empty, so new users and early sessions see generic output.
- `LlmEngine::decompose_task_with_feedback` and
  `LlmEngine::extract_tasks_with_feedback` thread examples through
  to the builder. The old one-arg variants are preserved and now
  call through with an empty slice.
- 4 unit tests covering empty, empty-input-skip, correction-wins,
  and thumbs-up-only fallback.

Tauri (src-tauri):
- New commands::feedback module: `record_feedback`,
  `list_feedback_examples_cmd`.
- `decompose_and_store` and `extract_tasks_from_transcript_cmd`
  now fetch the last 5 positive/neutral feedback rows for their
  target type and pass them through to the LLM, wiring the
  learning loop end-to-end.
- Shared `to_llm_examples` helper parses the `context_json.input`
  field (where the recorder stashes the parent task text / transcript
  chunk) back into the exemplar shape.

Frontend (MicroSteps.svelte):
- Thumbs-up and thumbs-down buttons on every micro-step row.
  Hover-revealed; the vote recolours the icon; clicking again
  clears the local highlight (the row itself stays in the audit
  trail).
- Pencil icon + double-click to edit step text. Save flows through
  update_task_cmd for persistence and records a correction feedback
  row with (original_text, corrected_text) — the highest-value
  training signal.
- Parent task text is captured in context_json.input at record time
  so the prompt builder can reconstruct the (input, preferred-output)
  pair on subsequent decompositions.
- Feedback capture is best-effort — a record_feedback failure never
  interrupts the primary action.

What's deferred to a later phase:
- Thumbs + corrections on extracted tasks (same pipeline, different
  surface — probably TasksPage after the AI-extraction path)
- Thumbs on transcript cleanup output
- Semantic retrieval over the feedback corpus (once there is enough
  data to justify embedding infrastructure; the storage shape is
  already ready for it)

src/lib/components/MicroSteps.svelte

@@ -1,8 +1,8 @@
 <script lang="ts">
   import { invoke } from '@tauri-apps/api/core';
-  import { ListTree, Check, Timer, Loader2 } from 'lucide-svelte';
+  import { ListTree, Check, Timer, Loader2, ThumbsUp, ThumbsDown, Pencil } from 'lucide-svelte';
 
-  let { parentTaskId, reduceMotion = false } = $props();
+  let { parentTaskId, parentTaskText = '', reduceMotion = false } = $props();
 
   interface Subtask {
     id: string;
@@ -15,6 +15,15 @@
   let error = $state('');
   let decomposing = $state(false);
 
+  // Per-step UI state. Keyed by subtask id so we never lose state when
+  // the list reorders. Values:
+  //   rating[id] — 1 | -1 — the thumbs vote the user gave this session
+  //   editing[id] — true while the user is editing the step text
+  //   draft[id]   — the in-flight edit value before save
+  let rating = $state<Record<string, 1 | -1 | undefined>>({});
+  let editing = $state<Record<string, boolean>>({});
+  let draft = $state<Record<string, string>>({});
+
   async function loadSubtasks() {
     loading = true;
     error = '';
@@ -53,6 +62,88 @@
     }));
   }
 
+  // --- HITL feedback --------------------------------------------------------
+  //
+  // All three paths (thumbs up, thumbs down, correction-via-edit) route
+  // into the same `record_feedback` command. The parent task text is the
+  // "input" the AI was given, so it travels in context_json so the prompt
+  // builder can reconstruct the (input, good-output) pair.
+
+  function feedbackContextJson() {
+    return JSON.stringify({ input: parentTaskText ?? '' });
+  }
+
+  async function recordThumb(step: Subtask, ratingValue: 1 | -1) {
+    // Toggle: if the user already voted the same way, clear it (record
+    // rating 0 means correction, not a thumb-off — we just skip the
+    // re-record and drop the local highlight). Unvoting isn't stored;
+    // the audit trail stays immutable.
+    if (rating[step.id] === ratingValue) {
+      const next = { ...rating };
+      delete next[step.id];
+      rating = next;
+      return;
+    }
+    rating = { ...rating, [step.id]: ratingValue };
+    try {
+      await invoke('record_feedback', {
+        input: {
+          targetType: 'microstep',
+          targetId: step.id,
+          rating: ratingValue,
+          originalText: step.text,
+          correctedText: null,
+          contextJson: feedbackContextJson(),
+        },
+      });
+    } catch (_) { /* feedback capture is best-effort, never fatal */ }
+  }
+
+  function startEdit(step: Subtask) {
+    editing = { ...editing, [step.id]: true };
+    draft = { ...draft, [step.id]: step.text };
+  }
+
+  function cancelEdit(stepId: string) {
+    const nextE = { ...editing }; delete nextE[stepId]; editing = nextE;
+    const nextD = { ...draft }; delete nextD[stepId]; draft = nextD;
+  }
+
+  async function saveEdit(step: Subtask) {
+    const next = (draft[step.id] ?? '').trim();
+    cancelEdit(step.id);
+    if (!next || next === step.text) return;
+    const original = step.text;
+    // Update in-memory first so the UI is snappy; roll back if the
+    // persistence call fails so we never show stale-but-different text.
+    const idx = subtasks.findIndex(s => s.id === step.id);
+    if (idx >= 0) subtasks[idx] = { ...subtasks[idx], text: next };
+    try {
+      await invoke('update_task_cmd', {
+        id: step.id,
+        patch: { text: next },
+      });
+      // Record correction as the highest-value feedback signal.
+      await invoke('record_feedback', {
+        input: {
+          targetType: 'microstep',
+          targetId: step.id,
+          rating: 0,
+          originalText: original,
+          correctedText: next,
+          contextJson: feedbackContextJson(),
+        },
+      }).catch(() => {});
+    } catch (_) {
+      if (idx >= 0) subtasks[idx] = { ...subtasks[idx], text: original };
+    }
+  }
+
+  function handleEditKeydown(evt: KeyboardEvent, step: Subtask) {
+    if (evt.key === 'Enter') { evt.preventDefault(); saveEdit(step); }
+    else if (evt.key === 'Escape') { evt.preventDefault(); cancelEdit(step.id); }
+  }
+
   $effect(() => {
     if (parentTaskId) loadSubtasks();
   });
@@ -97,10 +188,64 @@
             <Check size={9} aria-hidden="true" />
           {/if}
         </button>
-        <span class="text-[12px] flex-1 min-w-0 {step.done ? 'line-through text-text-tertiary' : 'text-text-secondary'} truncate">
-          {step.text}
-        </span>
-        {#if !step.done}
+
+        {#if editing[step.id]}
+          <!-- svelte-ignore a11y_autofocus — deliberate: inline edit
+               is user-initiated and focus must land on the input to
+               match the UX pattern users expect from any task app. -->
+          <input
+            type="text"
+            bind:value={draft[step.id]}
+            onkeydown={(e) => handleEditKeydown(e, step)}
+            onblur={() => saveEdit(step)}
+            class="text-[12px] flex-1 min-w-0 bg-bg-input border border-accent rounded px-1.5 py-0.5 text-text focus:outline-none"
+            autofocus
+            data-no-transition
+          />
+        {:else}
+          <button
+            type="button"
+            class="text-[12px] flex-1 min-w-0 {step.done ? 'line-through text-text-tertiary' : 'text-text-secondary'} truncate text-left cursor-text bg-transparent border-0 p-0"
+            ondblclick={() => !step.done && startEdit(step)}
+            disabled={step.done}
+            aria-label="Double-click to edit this step"
+            title="Double-click to edit"
+          >{step.text}</button>
+        {/if}
+
+        {#if !step.done && !editing[step.id]}
+          <!-- HITL feedback: thumbs vote + pencil edit. All three
+               route into record_feedback and feed the prompt-conditioning
+               loop. See docs/roadmap/2026-04-23-... Phase 2. -->
+          <button
+            class="opacity-0 group-hover:opacity-100 p-0.5 text-text-tertiary hover:text-success
+              {rating[step.id] === 1 ? '!opacity-100 text-success' : ''}"
+            onclick={() => recordThumb(step, 1)}
+            aria-label={rating[step.id] === 1 ? 'Remove thumbs up' : 'Thumbs up — this is a good step'}
+            title="Thumbs up — train the model on this style"
+            style={reduceMotion ? '' : 'transition: opacity var(--duration-ui), color var(--duration-ui)'}
+          >
+            <ThumbsUp size={10} aria-hidden="true" />
+          </button>
+          <button
+            class="opacity-0 group-hover:opacity-100 p-0.5 text-text-tertiary hover:text-danger
+              {rating[step.id] === -1 ? '!opacity-100 text-danger' : ''}"
+            onclick={() => recordThumb(step, -1)}
+            aria-label={rating[step.id] === -1 ? 'Remove thumbs down' : 'Thumbs down — this misses the mark'}
+            title="Thumbs down — avoid this style"
+            style={reduceMotion ? '' : 'transition: opacity var(--duration-ui), color var(--duration-ui)'}
+          >
+            <ThumbsDown size={10} aria-hidden="true" />
+          </button>
+          <button
+            class="opacity-0 group-hover:opacity-100 p-0.5 text-text-tertiary hover:text-accent"
+            onclick={() => startEdit(step)}
+            aria-label="Edit this step (the correction trains future suggestions)"
+            title="Edit — this is the strongest training signal"
+            style={reduceMotion ? '' : 'transition: opacity var(--duration-ui)'}
+          >
+            <Pencil size={10} aria-hidden="true" />
+          </button>
           <button
             class="opacity-0 group-hover:opacity-100 flex items-center gap-1 text-[10px] text-text-tertiary hover:text-accent"
             onclick={() => startTimer(step.id)}

src/lib/components/WipTaskList.svelte

@@ -107,7 +107,7 @@
           </div>
           <!-- Micro-steps panel (expanded) -->
           {#if expandedTaskIds.has(task.id)}
-            <MicroSteps parentTaskId={task.id} />
+            <MicroSteps parentTaskId={task.id} parentTaskText={task.text} />
           {/if}
         </div>
       {/each}