Revert the app to v0.1.34

.claude/skills/project-guardrails/SKILL.md

@@ -23,26 +23,15 @@ one, stop and ask the user first. This is the fast "don't" list; AGENTS.md's
 
 - **No streaming STT.** The AssemblyAI Sync API returns the full transcript in
   one response. Overlay goes "Transcribing…" → full text.
-- **No separate LLM cleanup pass.** Cleanup rides in the dictation request's
-  server-side `llm` block (`TranscriptionSteering`). No LLM Gateway client, no
+- **No separate LLM cleanup pass.** Cleanup rides in the Sync STT request's
+  `config.prompt` (`TranscriptionPrompt`). No LLM Gateway client, no
   `StylerProtocol`, no post-transcription styling stage.
 - **No local models / model downloads.** Transcription is a remote AssemblyAI
   call. No on-device ASR/LLM, no model cache, no download UI.
-- **Never send `config.prompt`.** It takes a _description of the audio_, not
-  instructions, and a custom value replaces the service's managed default
-  including its language steering. Vocabulary goes in `keyterms_prompt`, the
-  text before the cursor in `conversation_context`. An imperative like
-  "Transcribe speech into markdown." in `prompt` is a measured no-op — that is
-  exactly why those fields exist.
-- **Never send anything about the frontmost app.** `AppKindPriming` recognized
-  the app's bundle ID as a kind (terminal, code editor, Slack, Obsidian) and
-  sent a formatting clause as `llm.instruction`; the whole path was removed.
-  The bundle ID isn't captured, and `llm` always goes out empty so the
-  service's default cleanup rewrite applies everywhere.
-- Don't reintroduce a "remove filler words (um, uh, like)" directive — the STT
-  prompt doesn't act on it; it was deliberately dropped, and disfluency removal
-  is the LLM rewrite's job. Same for a language directive: pinning to English
-  hurt non-English speech, so language is left to the model's own detection.
+- Don't reintroduce a "remove filler words (um, uh, like)" directive in the
+  prompt — `universal-3-5-pro` ignores it; it was deliberately dropped. Same for
+  a language directive: pinning the prompt to English hurt non-English speech, so
+  language is left to the model's own detection.
 - **Injection is always a clipboard paste** (save → write → ⌘V → settle →
   restore), degrading to "left it on the clipboard" when the target is lost. No
   keystroke-by-keystroke typing path, no length threshold.

App/Blurt/Blurt/Info.plist

@@ -17,9 +17,9 @@
 	<key>CFBundlePackageType</key>
 	<string>APPL</string>
 	<key>CFBundleShortVersionString</key>
-	<string>0.1.36</string>
+	<string>0.1.34</string>
 	<key>CFBundleVersion</key>
-	<string>37</string>
+	<string>35</string>
 	<key>LSApplicationCategoryType</key>
 	<string>public.app-category.productivity</string>
 	<key>LSMinimumSystemVersion</key>

App/Blurt/Blurt/Wizard/Steps/KeyTermsStepView.swift

@@ -3,8 +3,8 @@ import SwiftUI
 
 /// The "Key Terms" section of the Settings window: a free-text
 /// area where the user lists comma-separated domain words (names, jargon, product
-/// names). These ride on every request as its `keyterms_prompt` vocabulary list
-/// (see `KeyTermsStore` / `TranscriptionSteering.build`), so the model favors those
+/// names). These are folded into every transcription's prompt as spelling priming
+/// (see `KeyTermsStore` / `TranscriptionPrompt.build`), so the model favors those
 /// spellings. Optional — it never gates setup; an empty list just sends no terms.
 struct KeyTermsStepView: View {
   /// Stored in UserDefaults so multiple settings windows/readers see edits live.

App/Blurt/project.yml

@@ -91,8 +91,8 @@ targets:
       properties:
         CFBundleName: Blurt
         CFBundleDisplayName: Blurt
-        CFBundleVersion: "37"
-        CFBundleShortVersionString: "0.1.36"
+        CFBundleVersion: "35"
+        CFBundleShortVersionString: "0.1.34"
         LSMinimumSystemVersion: "15.0"
         LSApplicationCategoryType: public.app-category.productivity
         NSMicrophoneUsageDescription: Blurt uses your microphone to transcribe your dictation with AssemblyAI.

BLURTENGINE.md

@@ -59,7 +59,7 @@ press() ──▶ MicCapture.start()            release() ──▶ MicCapture.s
 Key properties of the design, which your integration can rely on:
 
 - **One request per utterance, no streaming.** The dictation API returns the complete transcript — and its LLM-rewritten form — in the response body: no upload step, no job polling, no incremental deltas, no second request for the cleanup. `TranscriberProtocol.transcribe` is a single `async throws -> String`. UIs should show a "transcribing…" state and then the whole result; there is nothing to stream.
-- **Cleanup happens server-side.** The request's `llm` block asks the service for a cleanup rewrite (remove disfluencies, fix punctuation), applied to the verbatim transcript inside the same call; it always goes out empty, which selects the service's own default cleanup instruction. Recognition is primed separately by `conversation_context` and `keyterms_prompt` (built by `TranscriptionSteering` from the captured context); `config.prompt` is never sent, and neither is anything describing the destination app. The engine pastes `llm_response`, falling back to the verbatim `text` when the best-effort rewrite failed (`llm_error`) — a degradation, never a user-facing error. There is no client-side LLM pass, no styling stage, and deliberately no hook for one.
+- **Cleanup happens server-side.** The request's empty `llm` block asks the service for its default cleanup rewrite (remove disfluencies, fix punctuation), applied to the verbatim transcript inside the same call; the per-utterance `config.prompt` (built by `TranscriptionPrompt` from the captured context) primes the _transcription_. The engine pastes `llm_response`, falling back to the verbatim `text` when the best-effort rewrite failed (`llm_error`) — a degradation, never a user-facing error. There is no client-side LLM pass, no styling stage, and deliberately no hook for one.
 - **Latency is pre-paid where possible.** `press()` fires a detached `warmUp()` at the transcriber (pre-opening the HTTPS connection while the user speaks, ~170 ms saved cold) and kicks off the cross-process accessibility read of the focused field without awaiting it — the read is then consumed at transcribe time with a bounded wait (`DictationSession.contextWaitBudget`, 500 ms), so an unresponsive frontmost app costs the transcript its priming, never a multi-second stall — and never delays the recording indicator. On the way out, `release()` flips the phase to `.transcribing` _before_ reading the recorded audio back, so a host's stop cue fires at key-up rather than after the disk read.
 - **A held trigger auto-releases.** `DictationSession` stops recording after `maxRecordingSeconds` (default `SyncSTTLimits.autoReleaseSeconds`, 115 s) so audio never exceeds what the endpoint accepts, and transcribes what it has. Clips shorter than `SyncSTTLimits.minPCMBytes` (~100 ms of audio — an accidental tap) are dropped as a silent no-op rather than sent to earn a 400.
 
@@ -152,15 +152,15 @@ The session calls `setTargetApp` at press time with the app that was frontmost w
 
 Recognition quality comes from per-utterance priming, assembled automatically inside `press()` — hosts don't call these APIs directly, but should know what's collected:
 
-- **`TranscriptionContext`** carries the frontmost app name, window title, focused-field label, the text before the caret, the selected text (which a paste will replace), and the user's key terms. It's captured via Accessibility at press time (skipped in secure fields), off the hot path — and consumed at transcribe time with a bounded wait (`DictationSession.contextWaitBudget`), so a hung read is abandoned rather than stalling the transcript. Only the prior text and key terms reach the request; the prior text and window title also steer the injector's paste separator, and nothing else is consumed.
-- **`TranscriptionSteering.build(context:)`** renders that into the request's two customization fields: the prior-cursor text as the single `conversation_context` turn (clipped to 4096 chars keeping the tail, since the words nearest the cursor carry the continuity) and the user's key terms as `keyterms_prompt` (whole terms fitted to 2048 chars total). **`config.prompt` is never sent**: it takes a description of the audio rather than instructions, and a custom value replaces the service's managed default including its language steering, which is why the key terms ride in their own field. Nothing else is rendered — no app/field names, no selected text (the paste replaces it), and no standing annotation-suppression clause ("Transcribe without speaker labels, …" is part of the service's own default). Empty fields are omitted rather than sent as `[]`. Three further deliberate omissions: no language directive, no "remove filler words" clause (not something the STT prompt acts on — a no-op), and nothing identifying the destination app — an earlier `AppKindPriming` sent a bundle-ID-derived formatting clause as `llm.instruction`, and that whole path was removed. Don't reintroduce any of them.
+- **`TranscriptionContext`** carries the frontmost app name, window title, focused-field label, the text before the caret, the selected text (which a paste will replace), and the user's key terms. It's captured via Accessibility at press time (skipped in secure fields), off the hot path — and consumed at transcribe time with a bounded wait (`DictationSession.contextWaitBudget`), so a hung read is abandoned rather than stalling the transcript.
+- **`TranscriptionPrompt.build(context:)`** renders that into the dictation request's `config.prompt` (transcription steering only — the cleanup rewrite is the separate `llm` block), opening with the fixed `baseInstruction` ("Transcribe without speaker labels, audio event descriptions, or emotion markers.") and staying under the API's 4096-character cap. An empty context yields `nil`, which omits the field so the server applies its own default. Two deliberate omissions, both regression-tested: no language directive (pinning to English hurt non-English speech) and no "remove filler words" clause (not in the model's trained instruction set — a no-op). Don't reintroduce either.
 - **`KeyTermsStore`** persists the user's domain vocabulary (names, jargon) in `UserDefaults`; `DictationSession` re-reads it at every press via its `keyTermsProvider` closure, so Settings edits apply to the next utterance without rebuilding the session. Pass your own provider to source terms from elsewhere.
 
 For key storage, compose against **`APIKeyGateway`** — the injectable `current` / `save(_:)` / `hasKey` seam over the key store. `ProductionAPIKeyStore` forwards to the Keychain-backed `APIKeyStore`; `InMemoryAPIKeyStore` is a ready-made in-memory conformance for tests and harnesses (Blurt's XCUITest runs use it so the real Keychain item is never touched, and its `hasKey` backs the session's `readinessCheck`). For a settings UI, **`APIKeySubmission`** wraps the gateway with the validate-then-save flow (`submit(_:)` → valid / invalid / unreachable / saveFailed, via `APIKeyValidator`): it saves only a key AssemblyAI actively accepts, so an unverified key never persists. Two projections keep the surrounding UI out of your views: `Outcome.failureReport` classifies a failure as `.inline(message:)` (recoverable — show it beside the field) or `.alert(title:message:)` (a Keychain fault retyping can't fix), and **`APIKeyDisplay.resolve(key:)`** renders the stored key for an account row — masked tail, status and VoiceOver wording, and the connect-vs-rotate control titles. The mask reveals only the last `revealedTailLength` characters and, below `minimumLengthToMask`, none at all, so a short key can't be shown whole.
 
 Setup gating has a projection too: **`SetupReadiness.isReady(permissions:hasAPIKey:)`** is the "fully configured" rule (deliberately excluding the trigger key, which has a default), `SetupReadiness.pollInterval(isReady:)` is the permission-poll cadence (brisk during setup, coasting once ready), and `PermissionStatus.lostGrant(since:)` detects a permission revoked out from under a configured app.
 
-Each completed dictation is appended to **`DictationLog`** (a local JSONL history at `~/Library/Logs/Blurt/dictations.jsonl` — `DictationLog.defaultURL`, or `defaultDisplayPath` for the home-abbreviated form to show in UI) — each entry is the transcript plus the exact steering fields sent (`conversation_context`, `keyterms_prompt`), never the context that wasn't sent — but only while developer mode is switched on. **`DeveloperModeStore`** persists that opt-in in `UserDefaults` (`BlurtDeveloperMode`, off by default); with it off, nothing is written to disk. Blurt surfaces the switch (and the log path) in the Settings window's Developer section.
+Each completed dictation is appended to **`DictationLog`** (a local JSONL history at `~/Library/Logs/Blurt/dictations.jsonl` — `DictationLog.defaultURL`, or `defaultDisplayPath` for the home-abbreviated form to show in UI) with its context snapshot — but only while developer mode is switched on. **`DeveloperModeStore`** persists that opt-in in `UserDefaults` (`BlurtDeveloperMode`, off by default); with it off, nothing is written to disk. Blurt surfaces the switch (and the log path) in the Settings window's Developer section.
 
 ## Hotkey building blocks
 
@@ -195,7 +195,7 @@ Run `swift test` for the engine suites (`--filter DictationSessionTests` for one
 Each of these was tried the other way and reverted; the longer stories are in [AGENTS.md](AGENTS.md) and the source comments:
 
 - **No external SPM dependencies in the engine.** Foundation/Security/AVFoundation only.
-- **No streaming STT, no local models, no client-side LLM cleanup pass.** One dictation request per utterance is the architecture; the cleanup rewrite is server-side (the request's `llm` block), and request steering belongs in `TranscriptionSteering`.
+- **No streaming STT, no local models, no client-side LLM cleanup pass.** One dictation request per utterance is the architecture; the cleanup rewrite is server-side (the request's `llm` block), and transcription steering belongs in `TranscriptionPrompt`.
 - **No `AVAudioEngine`/`installTap` capture path.** Fresh `AVAudioRecorder` per session, resolved at record time.
 - **Paste is always clipboard-based** (save → write → ⌘V → settle → restore), with the copied-to-clipboard degradation for lost targets.
 - **No English-pinning or filler-word clauses in the prompt.**

README.md

@@ -166,14 +166,14 @@ Sources/BlurtEngine/     Swift 6 package owning the pipeline — no external dep
   Audio/                 MicCapture: fresh AVAudioRecorder per session, 16 kHz mono PCM,
                          live level meter; DX7/Juno-106 sound packs
   STT/                   AssemblyAITranscriber: one POST to dictation.assemblyai.com/transcribe
-                         (STT + LLM rewrite) + TranscriptionSteering context/keyterms
+                         (STT + LLM rewrite) + TranscriptionPrompt contextual priming
   Pipeline/              DictationSession actor: press/release/cancel commands, phase
                          stream, auto-release before the API's recording cap
   Hotkey/                DictationKeyGate/Router: pure, unit-tested state machine for the
                          lone-modifier trigger (tap vs hold vs combo)
   Injection/             KeyInjector: save clipboard → paste via synthesized ⌘V → restore
-  FocusCapture/          Accessibility reads of the focused app/window/field feeding the
-                         request's steering fields, the log, and paste separators
+  FocusCapture/          Accessibility reads of the focused app/window/field that prime
+                         the transcription prompt
   Config/, Update/       Keychain API-key store, key terms, download-only release check
 
 App/Blurt/               AppKit/SwiftUI shell (Xcode project generated by XcodeGen)

Sources/BlurtEngine/Config/KeyTermsStore.swift

@@ -1,9 +1,9 @@
 import Foundation
 
 /// Storage for the user's dictation "key terms" — a comma-separated list of
-/// domain words (names, jargon, product names) sent as the dictation request's
-/// `keyterms_prompt` vocabulary list, so the model is more likely to spell
-/// them correctly (see `TranscriptionSteering.build`).
+/// domain words (names, jargon, product names) that get folded into the dictation
+/// request `prompt` as vocabulary priming, so the model is more likely to spell
+/// them correctly (see `TranscriptionPrompt.build`).
 ///
 /// Unlike the API key these aren't secret, so they live in `UserDefaults` rather
 /// than the Keychain. The transcription pipeline reads the parsed list via
@@ -37,7 +37,7 @@ public enum KeyTermsStore {
   }
 
   /// Pure parse of a comma-separated string into a clean term list. Exposed so
-  /// `TranscriptionSteering` and tests can reuse the exact same rules.
+  /// `TranscriptionPrompt` and tests can reuse the exact same rules.
   public static func parse(_ text: String?) -> [String] {
     guard let text else { return [] }
     var seen = Set<String>()

Sources/BlurtEngine/FocusCapture/FocusCapture.swift

@@ -10,25 +10,27 @@ enum FocusCapture {
   @MainActor
   static func captureFrontmost() -> CapturedFocus? {
     guard let app = NSWorkspace.shared.frontmostApplication else { return nil }
-    return CapturedFocus(pid: app.processIdentifier, processName: app.localizedName)
+    return CapturedFocus(
+      pid: app.processIdentifier,
+      processName: app.localizedName
+    )
   }
 
   static func runningApp(for captured: CapturedFocus) -> NSRunningApplication? {
     NSRunningApplication(processIdentifier: captured.pid)
   }
 
-  /// Accessibility-derived focus context read from the system-wide focused UI
-  /// element at dictation start (see `TranscriptionContext` for what each
-  /// signal feeds). Every field is best-effort: any signal that can't be read
-  /// is `nil`, and a fully-empty result simply means less context, never an
-  /// error.
+  /// Accessibility-derived priming read from the system-wide focused UI element
+  /// at dictation start (see `TranscriptionContext`). Every field is
+  /// best-effort: any signal that can't be read is `nil`, and a fully-empty
+  /// result simply means less context, never an error.
   struct FocusedFieldContext: Sendable {
-    /// Text immediately preceding the insertion point.
+    /// Text immediately preceding the insertion point ("prior chunk context").
     let priorText: String?
     /// The text currently selected in the focused field — the dictation will
-    /// replace it.
+    /// replace it, so it primes the model on what the utterance is about.
     let selectedText: String?
-    /// The focused window's title (in a code editor it names the open file).
+    /// The focused window's title — a dense topic hint.
     let windowTitle: String?
     /// A short label for the focused field ("To", "Search", "Message").
     let fieldLabel: String?
@@ -47,8 +49,8 @@ enum FocusCapture {
   ///
   /// Secure text fields (password inputs) are detected by role **or** subrole and
   /// never have their contents read, so a typed password — selected or not — can't
-  /// leak into the dictation log or the injector. The check fails closed: an
-  /// unreadable role is treated as secure, since it can't be shown not to be.
+  /// leak into the STT prompt. The check fails closed: an unreadable role is
+  /// treated as secure, since it can't be shown not to be.
   ///
   /// Deliberately `nonisolated`: each read below is a synchronous cross-process
   /// IPC round trip into the frontmost app, and an unresponsive app blocks the