Why is this happening? I wanted to test a non-answer, then it did a great job of nudging me for an answer. Now it took a while to understand that I said “I don't know” and it didn't acknowledge my answer. Why is this happening?

Thanks for reaching out, Ganesh. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

LayerComponentVersion/DetailFrameworkLiveKit Agents SDKlivekit-agents[silero,turn-detector]~=1.2STTDeepgram Nova-3via livekit-plugins-deepgram~=1.2, interim_results=True, endpointing_ms=500TTSElevenLabsvoice ID AONNTSthM6ici6gcQRBxLLMOpenAI GPT-4o-minitemperature=0.0 (used only for response analysis, not question delivery)VADSilero VADmin_silence_duration=0.4, activation_threshold=0.35 (dynamically raised to 1.2s for qualitative Qs)Turn Detectionserver_vadAvatarAnam AIID 69debf85-...CloudLiveKit appweb/templates/survey.htmlOSmacOS (darwin)multiprocessing set to forkserver This is a custom guided survey/focus-group agent -- not a freeform chatbot. Questions are delivered via direct TTS (bypassing LLM), and responses are captured through STT events + polling loops. 2. Detailed Timeline Analysis -- Why Your Answer Didn’t Register Here’s the exact event trace for Q#2 (T1): Phase A: Question Delivery (worked fine) 165948.993 -- TTS START: “Ganesh, Have you ever commissioned or participated in opinion research before...” • 165959.885 -- TTS END, 10.9s, not truncated. Delivery state -> delivered • 165959.898 -- Polling begins. Timeout monitoring starts (prompt at 10s, skip at 20s) Phase B: Your 14-second silence (working as designed) 170000 -- 170009 -- Polling checks 0-90, user_msgs=0. You were silent. 170009.902 -- 10-second timeout fires: “No response from ganesh after 10 seconds, prompting...” • Agent says via TTS: “Ganesh, please let me know what you think.” Phase C: Your FIRST speech attempt -- STT DROPPED IT 170013.582 -- user_state_changed: listening -> speaking (VAD detected you) 170014.631 -- The prompt TTS playback finishes 170015.382 -- user_state_changed: speaking -> listening (you spoke for 1.8 seconds) • 170015.888 -- “No user messages in context yet” There is NO user_input_transcribed event between 170013 and 170015. VAD correctly detected 1.8s of speech, but Deepgram produced zero transcription. This is the first STT dropout. Phase D: 8 seconds of silence, then your SECOND speech attempt -- STT WORKED 170016 -- 170022 -- Polling checks 160-220, still user_msgs=0 170023.334 -- You started speaking again 170023.505 -- user_input_transcribed: “I don’t” (STT working now!) 170024.608 -- user_input_transcribed: “I don’t know.” 170025.133 -- You stopped speaking (1.8s of speech) • 170026.733 -- Response captured: “I don’t know.” Phase E: Encouragement prompt -- app-level bug causes cascade 170026.746 -- Uncertain response detected, encouragement triggered • 170034.648 -- Agent says: “Are you sure, Ganesh? There’s no right or wrong answer here. Feel free to share whatever comes to mind, even if it’s just a quick thought.” • 170034.649 -- Reset turn monitoring • But the reset is incomplete: The encouragement handler resets these (lines 2846-2848): moderator_agent.py Lines 2846-2848 self.latest_user_response = None self.response_captured = False self.last_stt_fragment = “” But it does NOT reset: • pending_stt_transcript -- still contains “I don’t know.” from before • _first_vad_speaking_time -- still set from 21 seconds ago Phase F: False STT health check fires IMMEDIATELY • 170034.754 -- “STT HEALTH CHECK: VAD detected speech 21s ago but no STT transcripts received for ganesh! Nudging participant.” Because _first_vad_speaking_time wasn’t reset, the health check thinks STT has been broken for 21 seconds and fires a nudge: “I’m sorry Ganesh, I couldn’t quite hear you. Could you please repeat that a bit louder?” This is the false/confusing extra prompt you heard. Phase G: Your THIRD speech attempt -- STT DROPPED IT AGAIN • 170035.832 -- You started speaking (trying to answer after “Are you sure?“) • 170037.383 -- You stopped speaking (1.6 seconds of speech) Again, NO user_input_transcribed event between 170035 and 170037. Second STT dropout. 170037.887 -- Immediate capture fires, but grabs the stale pending_stt_transcript = “I don’t know.” from Phase D • 170039.521 -- encouragement_given: True, so it accepts the stale “I don’t know.” as final • 170043 -- Moves on to Q#3 Your actual second answer was never heard. It was lost to the STT dropout, and the system re-captured the old “I don’t know.” from the un-cleared buffer. 3. Settings and Prompts That Fired TriggerTimingExact Text Spoken10s no-response timeout170009.902_"Ganesh, please let me know what you think.“_Uncertain response encouragement170034.648_”Are you sure, Ganesh? There’s no right or wrong answer here. Feel free to share whatever comes to mind, even if it’s just a quick thought.“_False STT health nudge170034.754_"I’m sorry Ganesh, I couldn’t quite hear you. Could you please repeat that a bit louder?”_ Relevant enabled settings: Timeout monitoring: prompt at 10s, skip at 20s (monitor_response_timeout) Uncertain response detection: triggers for phrases like “I don’t know” with no substantive content Encouragement: one retry allowed, then accepts answer on second uncertain response STT health check: fires if VAD saw speech 15+ seconds ago but no STT transcripts arrived VAD dynamic tuning: min_silence_duration=1.2s for qualitative questions • Deepgram config: interim_results=True, endpointing_ms=500, smart_format=True, punctuate=True

Thanks — this is very helpful detail. I’ll walk through what happened, why your “I don’t know” wasn’t accepted immediately, and practical changes you can make to reduce or eliminate this behavior. I’ll keep it focused on the three root issues shown in your trace: the STT dropout, the encouragement (uncertainty) detection, and the app-level reset that retriggered nudging. Quick summary of what happened • Your first short utterance (170013–170015, ~1.8s) was detected by VAD but Deepgram returned no transcription (STT dropout). Because no transcribed user message reached the agent, the system treated the turn as still unanswered. • Your second utterance (170023–170025) was transcribed correctly as “I don’t know.” That transcription arrived and was captured. • Immediately after capture, the agent’s “uncertain response” detection flagged the content as low-information and triggered an encouragement prompt. The encouragement logic then reset turn monitoring and continued nudging. Why each problem occurred and recommended fixes 1) STT dropout (VAD detected speech but Deepgram returned nothing) • Why it happened: VAD indicated speech but STT produced zero transcription for that short (~1.8s) utterance. Short utterances, microphone levels, brief clipping at the start/end, or Deepgram endpointing settings can cause missed transcriptions. • What to try: ◦ Increase

interim_results

sensitivity or lower

endpointing_ms

temporarily for short-turn capture testing. You currently have

interim_results=True

and `endpointing_ms=500`; verify Deepgram isn’t discarding very short utterances before sending a final transcript. ◦ Add a short buffer to VAD-to-STT handover so the STT request includes 100–300 ms pre-roll and post-roll audio around VAD segments (helps if speech started/ended near VAD thresholds). ◦ Log raw audio clips for missed VAD->no-transcript events to inspect level/clipping. ◦ If network jitter or request retries are possible, add a retry path for STT when VAD detected speech but no transcription is returned within X ms (e.g., 300–500 ms). 2) Uncertain-response detection flagged “I don’t know” • Why it happened: The agent classifies low-content replies (e.g., “I don’t know,” “not sure”) as uncertain and triggers encouragement prompts by design. That’s a content-level policy, independent of whether transcription succeeded earlier. • What to try: ◦ Adjust the uncertainty detector threshold or rules so that explicit non-answers like “I don’t know” are treated as valid terminal responses rather than prompts for elaboration. ◦ Add a phrase whitelist: if transcription matches exact patterns like “I don’t know”, “no idea”, “I’m not sure”, treat as an accepted answer and skip encouragement. ◦ Alternatively, have the encouragement logic only run after N attempts or after no STT events at all; e.g., encourage only if there were 0 transcriptions for the whole turn OR if the user has provided multiple low-content responses across turns. 3) App-level reset caused nudging cascade • Why it happened: After the encouragement prompt fired the app reset turn monitoring immediately, which restarted timeout logic and kept nudging. That makes a single “I don’t know” trigger further prompts. • What to try: ◦ Change the state machine so that an encouragement prompt does not reset turn timers. Instead: ▪︎ Option A: Encourage and continue the same turn timer without reset (gives user time after encouragement). ▪︎ Option B: Treat encouragement as a final micro-prompt and accept the previous transcription if it matches a whitelist; only reset if there is no transcription after encouragement. ◦ Add a short “grace period” after receiving a transcription (e.g., 3–5s) during which encouragement logic is suppressed. Concrete small changes to try first (ordered) 1. Add exact-match whitelist handling: accept transcripts equal to common non-answers (

"I don't know"

,

"not sure"

,

"no idea"

) as final answers and do not run encouragement. This is the lowest-effort, highest-impact change. 2. Prevent encouragement from resetting the turn timer. Make encouragement non-destructive to turn state. This avoids cascades. 3. Add 200–300ms pre/post audio to STT requests and/or enable a small STT retry if VAD saw speech but no transcript arrives within 300ms. 4. If missed transcriptions persist, capture and inspect raw audio for those segments to check clipping/level/noise; consider increasing mic gain or changing VAD thresholds. Diagnostics I can help you run • I can help craft a short test that toggles whitelist behavior and logs outcomes for 10 repeated short non-answers so you can measure improvement. • I can provide a minimal change to the encouragement state machine (pseudo-state transitions) if you want an exact implementation pattern for “don’t reset timer on encouragement.” • If you can share a 10–20s raw audio clip from the VAD->no-transcript event, we can inspect whether the speech was clipped or too soft. Next step for you • Which fix would you like to try first? (Whitelist for exact non-answers, change encouragement not to reset timers, or STT pre/post-roll + retry.) • If you pick one, tell me whether you want a short test script and I’ll provide the steps/snippets you can plug into your agent. You’ve done great collecting the trace — with the whitelist + not-resetting-timer change you should see the behavior you expect: “I don’t know” accepted immediately and no repeated nudges.

LayerComponentVersion/DetailFrameworkLiveKit Agents SDKlivekit-agents[silero,turn-detector]~=1.2STTDeepgram Nova-3via livekit-plugins-deepgram~=1.2, interim_results=True, endpointing_ms=500TTSElevenLabsvoice ID AONNTSthM6ici6gcQRBxLLMOpenAI GPT-4o-minitemperature=0.0 (used only for response analysis, not question delivery)VADSilero VADmin_silence_duration=0.4, activation_threshold=0.35 (dynamically raised to 1.2s for qualitative Qs)Turn Detectionserver_vadAvatarAnam AIID 69debf85-...CloudLiveKit appweb/templates/survey.htmlOSmacOS (darwin)multiprocessing set to forkserver This is a custom guided survey/focus-group agent -- not a freeform chatbot. Questions are delivered via direct TTS (bypassing LLM), and responses are captured through STT events + polling loops. 2. Detailed Timeline Analysis -- Why Your Answer Didn’t Register Here’s the exact event trace for Q#2 (T1): Phase A: Question Delivery (worked fine) 165948.993 -- TTS START: “Ganesh, Have you ever commissioned or participated in opinion research before...” • 165959.885 -- TTS END, 10.9s, not truncated. Delivery state -> delivered • 165959.898 -- Polling begins. Timeout monitoring starts (prompt at 10s, skip at 20s) Phase B: Your 14-second silence (working as designed) 170000 -- 170009 -- Polling checks 0-90, user_msgs=0. You were silent. 170009.902 -- 10-second timeout fires: “No response from ganesh after 10 seconds, prompting...” • Agent says via TTS: “Ganesh, please let me know what you think.” Phase C: Your FIRST speech attempt -- STT DROPPED IT 170013.582 -- user_state_changed: listening -> speaking (VAD detected you) 170014.631 -- The prompt TTS playback finishes 170015.382 -- user_state_changed: speaking -> listening (you spoke for 1.8 seconds) • 170015.888 -- “No user messages in context yet” There is NO user_input_transcribed event between 170013 and 170015. VAD correctly detected 1.8s of speech, but Deepgram produced zero transcription. This is the first STT dropout. Phase D: 8 seconds of silence, then your SECOND speech attempt -- STT WORKED 170016 -- 170022 -- Polling checks 160-220, still user_msgs=0 170023.334 -- You started speaking again 170023.505 -- user_input_transcribed: “I don’t” (STT working now!) 170024.608 -- user_input_transcribed: “I don’t know.” 170025.133 -- You stopped speaking (1.8s of speech) • 170026.733 -- Response captured: “I don’t know.” Phase E: Encouragement prompt -- app-level bug causes cascade 170026.746 -- Uncertain response detected, encouragement triggered • 170034.648 -- Agent says: “Are you sure, Ganesh? There’s no right or wrong answer here. Feel free to share whatever comes to mind, even if it’s just a quick thought.” • 170034.649 -- Reset turn monitoring • But the reset is incomplete: The encouragement handler resets these (lines 2846-2848): moderator_agent.py Lines 2846-2848 self.latest_user_response = None self.response_captured = False self.last_stt_fragment = “” But it does NOT reset: • pending_stt_transcript -- still contains “I don’t know.” from before • _first_vad_speaking_time -- still set from 21 seconds ago Phase F: False STT health check fires IMMEDIATELY • 170034.754 -- “STT HEALTH CHECK: VAD detected speech 21s ago but no STT transcripts received for ganesh! Nudging participant.” Because _first_vad_speaking_time wasn’t reset, the health check thinks STT has been broken for 21 seconds and fires a nudge: “I’m sorry Ganesh, I couldn’t quite hear you. Could you please repeat that a bit louder?” This is the false/confusing extra prompt you heard. Phase G: Your THIRD speech attempt -- STT DROPPED IT AGAIN • 170035.832 -- You started speaking (trying to answer after “Are you sure?“) • 170037.383 -- You stopped speaking (1.6 seconds of speech) Again, NO user_input_transcribed event between 170035 and 170037. Second STT dropout. 170037.887 -- Immediate capture fires, but grabs the stale pending_stt_transcript = “I don’t know.” from Phase D • 170039.521 -- encouragement_given: True, so it accepts the stale “I don’t know.” as final • 170043 -- Moves on to Q#3 Your actual second answer was never heard. It was lost to the STT dropout, and the system re-captured the old “I don’t know.” from the un-cleared buffer. 3. Settings and Prompts That Fired TriggerTimingExact Text Spoken10s no-response timeout170009.902_"Ganesh, please let me know what you think.“_Uncertain response encouragement170034.648_”Are you sure, Ganesh? There’s no right or wrong answer here. Feel free to share whatever comes to mind, even if it’s just a quick thought.“_False STT health nudge170034.754_"I’m sorry Ganesh, I couldn’t quite hear you. Could you please repeat that a bit louder?”_ Relevant enabled settings: Timeout monitoring: prompt at 10s, skip at 20s (monitor_response_timeout) Uncertain response detection: triggers for phrases like “I don’t know” with no substantive content Encouragement: one retry allowed, then accepts answer on second uncertain response STT health check: fires if VAD saw speech 15+ seconds ago but no STT transcripts arrived VAD dynamic tuning: min_silence_duration=1.2s for qualitative questions • Deepgram config: interim_results=True, endpointing_ms=500, smart_format=True, punctuate=True

Thanks — this is an excellent, very detailed trace. I’ll keep this focused on next steps you can take and offer the exact change you tell me to prioritize. Ack and short summary of what went wrong • Your “I don’t know” was transcribed correctly once, but the encouragement flow triggered and partially reset state. Because a couple of internal fields (notably

pending_stt_transcript

and

_first_vad_speaking_time

) were not cleared, a STT-health check immediately misread the state and fired an extra nudge. • Two STT dropouts (short ~1.6–1.8s utterances) around the encouragement made the system re-use stale buffered text, so your actual later answer never made it into the final captured response. Which fixes will most directly stop this behavior • Whitelist exact non-answers (e.g., “I don’t know”, “not sure”, “no idea”) and accept them immediately. This is the lowest-effort, highest-impact fix. • Stop the encouragement handler from resetting turn timers/state in a way that leaves stale buffers. Make encouragement non-destructive to turn state (don’t reset

_first_vad_speaking_time

or

pending_stt_transcript

unless you clear them all). • Add a small STT safety/retry and pre/post-roll buffer so very short utterances aren’t lost. Recommended immediate change to try (I suggest this order) 1) Implement exact-match whitelist for terminal non-answers and skip encouragement for them. 2) Modify the encouragement handler so it does not reset timers/state in a way that leaves stale buffers — either: • Don’t reset

_first_vad_speaking_time

and

pending_stt_transcript

at all on encouragement, or • Reset all related fields together atomically (so you never leave a stale transcript when

last_vad

still points to an older time). 3) Add 200–300 ms pre-roll/post-roll to STT requests and a short retry if VAD detected speech but no transcript arrives within ~300–500 ms. If you want, I can provide code-level guidance for any of these. Pick one of the following and I’ll give a precise change you can drop into your code and a short test plan: • A: Whitelist exact non-answers (fastest). I’ll provide the matching logic and where to place it before uncertain-response handling. • B: Make encouragement non-destructive to turn state (fixes the cascade). I’ll provide the small atomic-reset pattern or state-machine change to avoid leaving stale

pending_stt_transcript

or

_first_vad_speaking_time

. • C: STT pre/post-roll + retry (addresses dropout). I’ll give the audio buffering/retry snippet and test steps. Also: quick test I recommend after changes 1. Run 10 reps of a short non-answer (“I don’t know”) delivered after a question; measure how many times encouragement fires. 2. Run 10 reps of very short utterances (~1.5–2.0s) to check STT dropouts before/after the buffering/retry change. 3. Confirm no stale transcript is accepted after an encouragement prompt. Which option would you like me to provide code/snippet and test steps for first — A (whitelist), B (non-destructive encouragement), or C (STT pre/post-roll + retry)?

Let’s do: A: Whitelist exact non-answers (fastest). I’ll provide the matching logic and where to place it before uncertain-response handling.

Thanks — great choice. Below is a concise, ready-to-drop implementation for whitelisting exact non-answers plus guidance on where to place it and a short test plan. What this does • Normalizes the STT text and checks for exact-match non-answer phrases. • If matched, accepts the response as terminal (records it as skipped/none) and bypasses any encouragement/uncertainty logic. • Runs early — before uncertain-response detection or encouragement handlers. Code snippet (place in your transcription handling / response processing path) • Add this near the top of the function that receives finalized transcriptions (e.g., in

process_user_response

, or immediately after

user_input_transcribed

is received), before any uncertainty/encouragement logic runs.

# Define once at module/class level
NON_ANSWER_PHRASES = {
    "i don't know",
    "i dont know",
    "no",
    "none",
    "n/a",
    "not applicable",
    "not sure",
    "unknown",
    "pass",
    "skip"
}

def normalize_text(s: str) -> str:
    return s.strip().lower()

def process_user_response(self, user_input: str):
    user_input_clean = normalize_text(user_input)

    # Early whitelist check — must come BEFORE uncertain-response handling
    if user_input_clean in NON_ANSWER_PHRASES:
        <http://logger.info|logger.info>(f"Non-answer detected and accepted: '{user_input}'")
        # Record as an explicit non-answer. Choose whichever internal representation you use:
        # Option 1: Record as a special value
        self.record_response({"value": None, "reason": "non_answer", "raw": user_input})
        # Option 2: Mark skipped (if your DB/model expects that)
        # self.record_response_skipped()
        # Ensure encouragement logic sees that a final response has been captured
        self.latest_user_response = user_input_clean
        self.response_captured = True
        # Clear any STT buffers to avoid stale reuse
        self.pending_stt_transcript = ""
        self.last_stt_fragment = ""
        return

    # ...existing uncertain-response detection and other processing continues here...

Placement notes • Put the check immediately after you set or receive the final transcription event (the

user_input_transcribed

handler) and before any code that: ◦ runs uncertain-response detectors, ◦ triggers encouragement prompts, or ◦ resets timers/state that could interact with

pending_stt_transcript

or

_first_vad_speaking_time

. • If you have multiple places that accept transcripts (immediate-capture + delayed-capture), ensure the whitelist runs in each path. Suggested small improvements to make whitelist robust • Use punctuation normalization (optional): remove punctuation before matching so “I don’t know.” still matches. • Expand phrases incrementally from logs: after deployment, inspect transcripts that caused encouragement and add common variants (e.g., “i dunno”, “i'm not sure”, “no idea”). • If you want more flexibility later, switch to simple pattern matching (e.g., regex for

^i\s*do(n'?t)?\s*know

), but start with exact-match for deterministic behavior. Short test plan 1. Unit test: ◦ Send exact strings from the

NON_ANSWER_PHRASES

set and assert

response_captured = True

and that encouragement is not triggered. 1. Integration test (in your app): ◦ Run 10 trials where participant replies with “I don’t know” right after the question. Verify no encouragement prompts and the response is recorded as non-answer. ◦ Run 10 trials of short utterances (~1.5–2.0s) that are NOT in the whitelist, and verify normal uncertain-response behavior still applies. 1. Logging: ◦ Temporarily increase logging around whitelist matches for 24–48 hours to capture missed variants for expansion. If you want, I can: • Provide a small regex alternative that covers common contractions and punctuation (safe but slightly broader). • Draft the exact change as a git patch for

moderator_agent.py

(if you tell me the function name that currently handles

user_input_transcribed

). Which follow-up would you like — a conservative regex that covers contractions (e.g.,

i dont

,

i'm not sure

) or the git patch for your

moderator_agent.py

? Sources: How to Test Your Agent Using Another Agent | LiveKit | How to test your agent using another agent

Can you create a prompt for me to put in Cursor’s Agent mode?

Below is a ready-to-use prompt you can paste into Cursor’s Agent mode. It tells the agent exactly what you want: detect exact non-answer phrases from STT, accept them as terminal responses, clear any STT buffers, and skip encouragement or nudging logic. It includes a concise code snippet and testing steps. Prompt for Cursor Agent mode You are an assistant that modifies a LiveKit-based guided survey agent. The agent receives finalized STT transcripts as strings. Implement an exact-match whitelist for short non-answer responses so they are accepted immediately (no encouragement, no retry nudges). Do this check as the very first step after receiving a finalized transcription. When a match is found, record the response as a non-answer (skipped) and clear STT buffers so stale transcripts aren’t reused. Requirements: • Match only normalized exact phrases (case-insensitive, trimmed). Do NOT run fuzzy matching or LLM classification for this step. • On match: ◦ Mark the response captured (so encouragement/uncertainty logic sees a final answer). ◦ Record the response as a non-answer/skipped in the same storage API your agent uses. ◦ Clear STT buffers:

pending_stt_transcript

,

last_stt_fragment

(or equivalents). ◦ Do not reset VAD timers like

_first_vad_speaking_time

unless you atomically clear all related state to avoid false STT-health triggers. • If no match, continue with normal processing (uncertainty detection, encouragement, etc.). Code snippet to insert at the top of your transcription handler (Python pseudocode — adapt variable names to your codebase):

# Whitelist of exact non-answer phrases
NON_ANSWER_PHRASES = {
    "i don't know",
    "i dont know",
    "no",
    "none",
    "n/a",
    "not applicable",
    "not sure",
    "unknown",
    "pass",
    "skip"
}

def normalize_text(s: str) -> str:
    return s.strip().lower()

def handle_final_transcript(self, transcript: str):
    cleaned = normalize_text(transcript)

    # Early whitelist check — must run BEFORE any encouragement/uncertainty logic
    if cleaned in NON_ANSWER_PHRASES:
        <http://logger.info|logger.info>(f"Whitelist non-answer accepted: '{transcript}'")

        # Record accepted non-answer in your storage/state
        # Example: record as skipped/non-answer
        self.record_response({"value": None, "reason": "non_answer", "raw": transcript})

        # Mark as captured so other handlers won't re-prompt
        self.latest_user_response = cleaned
        self.response_captured = True

        # Clear STT buffers so stale transcripts are not reused
        self.pending_stt_transcript = ""
        self.last_stt_fragment = ""

        # Optionally: do not reset VAD timers alone; if you must reset, reset related fields atomically
        # self._first_vad_speaking_time = None
        # self._last_vad_time = None

        return

    # If not a whitelist match, continue with existing logic
    self.run_uncertainty_detection_and_followups(transcript)

Testing steps to validate: 1. Unit test: send each exact phrase in NON_ANSWER_PHRASES to the handler and assert: ◦

response_captured

is True ◦

pending_stt_transcript

and

last_stt_fragment

are cleared ◦ Encouragement logic is not invoked 1. Integration: run 10 trials where an actor replies “I don’t know” immediately after a question. Verify the agent accepts it without prompt. 2. Log expansion: enable short-term logging of whitelist matches for 24–48 hours to capture additional variants (e.g., “i dunno”, “i'm not sure”) to add to the whitelist later. If you want a slightly more permissive pattern now, I can provide a conservative regex variant (covers common contractions and punctuation) — tell me if you’d like that regex included instead of exact-match.