Review and Message Responder

Runs on: reasoning - reads your files and reasons; any capable agent can run this.

You are drafting a reply to an incoming customer message. The message could be a public review, a private DM, a WhatsApp inquiry, an email, or any other inbound. The output is a draft reply in the right voice for the channel and the brand.

This skill is NOT a generic AI customer-service responder. It applies the operator's or brand's actual voice, respects channel constraints, and refuses to invent facts the operator has not provided.

If any are missing, ask. </Instruction-gate>

Phase 0 - Capture the incoming message

If the user has not pasted the message yet, ask:

Paste the incoming message exactly as it appears - including the customer's name, rating if any, and the channel it came from (Google Review, Instagram DM, WhatsApp, email, etc.). I will not respond well to a paraphrase.

If they only summarize, push once: "Paste the actual text. Tone and exact wording matter for the reply."

Capture as incoming.

If the customer name is visible, capture it. Address the customer by first name in the reply where the channel allows it (review platforms allow it, public ad replies might not).

Phase 1 - Whose voice?

Run: python scripts/list-brands.py if it exists. If not, glob brands/*/voice.yml.

If 0 brands exist:

• Default to operator voice.
• Say: "No brand voices captured yet. Reply will use your personal voice from core/voice-profile.yml. If this message came to a brand you run, set up brand-voice-interview first - operator voice on a brand channel signals inconsistency."
• Wait one beat for the user to confirm. If they say "use my voice anyway", proceed.

If 1+ brands exist:

• Ask:

  Whose voice should this reply use?

  1. You - your personal voice (operator).<list each brand by display_name>

  Pick by number or say a brand name.

Load the matching voice file:

• Operator: core/voice-profile.yml
• Brand: brands/<slug>/voice.yml + brands/<slug>/positioning.yml

Run the voice readiness check:

• Operator: python scripts/check-voice-ready.py
• Brand: python scripts/check-brand-voice-ready.py --brand <slug> if it exists

If the readiness gate fails, surface the message verbatim. Offer to proceed with anti-AI baseline only if the user confirms.

Phase 2 - Channel

Ask if not obvious from the paste:

Which channel is this on? (Google Review, Trustpilot, Instagram DM, WhatsApp Business, customer email, Facebook comment, Yelp, other.)

The channel sets:

• Length budget - WhatsApp/DM: 30-80 words. Google review: 50-120 words. Trustpilot: 80-150 words. Email: 100-300 words. Facebook comment: 30-80 words.
• Public vs private - public replies are also read by future customers, not just the sender.
• Formality floor - corporate review platforms have a higher formality floor than DMs.
• CTA shape - DM can link, WhatsApp can attach, review platforms usually cannot.

Capture as channel.

Phase 3 - Posture

Ask:

What is the right posture for this reply?

1. Warm thank-you - positive review, happy customer, just want to acknowledge.
2. Careful negative - complaint, negative review, public issue. Acknowledge, address what is true, offer a path forward without being defensive.
3. Factual answer - customer is asking a specific question (price, availability, hours, how-to). Answer the question, no more.
4. Soft sell - customer is curious but not committed. Answer their question AND surface the offer.
5. De-escalation - customer is angry. Lower the temperature first, address facts second, never argue.
6. Reactivation - customer is interested again after going dark. Re-establish the relationship before re-introducing the offer.
7. Custom - describe what you want.

Capture as posture. Different postures need different opening moves and CTA energy.

Phase 4 - Facts the user must supply

Before drafting, scan the incoming message for what would need to be answered. List back:

Before I draft, I need a few facts. Answer what you can. If you do not know one, say "skip" and I will leave it as a placeholder.

• <fact 1: e.g. is the customer's claim about the wait time accurate?>
• <fact 2: e.g. what is the price the customer is asking about?>
• <fact 3: e.g. what is the policy on the return they are requesting?>

Capture each fact. If a fact is not supplied, mark the draft with [FILL: <description>] at that spot. Do not invent.

If the posture is "careful negative" or "de-escalation", also ask:

Is anything in the customer's complaint factually wrong, or is the issue real? Tell me honestly - the reply changes based on whether we are acknowledging a true failure or correcting a misunderstanding.

This shapes whether the reply leads with acknowledgment or with a correction.

Phase 5 - Apply voice + register

Read the loaded voice file (operator or brand). Apply:

1. Run your-voice rules in full (read skills/your-voice/SKILL.md).
2. Adjust per register:
   • plain-direct - default. Short hits. Direct.
   • measured-elegant - sentences breathe. Allow craft vocabulary. Avoid contractions if profile says so.
   • corporate-restrained - formal close. Allow "we appreciate", "we will look into". Hedging allowed.
   • friendly-casual - contractions always on. Exclamation marks allowed (1 max). First-person warmth.
3. Apply channel format constraints (length, public vs private).
4. Apply posture template:
   • Warm thank-you: address by name, name what specifically you appreciated they noticed, close with an invitation back.
   • Careful negative: lead with acknowledgment of the specific thing (not generic "sorry to hear that"), state what is true that you can address, offer a concrete next step (DM, email, refund process), never defensive.
   • Factual answer: answer first, context second, no upsell unless asked.
   • Soft sell: answer first, then surface the offer in one sentence, then leave the door open.
   • De-escalation: lower the temperature in line 1 (no "we are sorry you feel that way" - that is provocation), name what is true in line 2, offer the move-it-private path in line 3.
   • Reactivation: warm recognition, no "long time no see", straight to what is new and relevant.
5. Apply anti-AI baseline (universal): no em dashes, no rule-of-three, no negation-contrast, no banned phrases.
6. If the brand positioning has regulatory.forbidden_claims, scan the draft for any matches and rewrite. (e.g. a financial brand cannot say "guaranteed returns" even in a customer reply.)

Phase 6 - Output

For PRIVATE channels (DM, WhatsApp, email), output:

DRAFT REPLY
===========
Channel: <channel>
Voice: <operator | brand display_name>
Posture: <posture>
Length: <word count> words

<draft>

NOTES
=====
- <any [FILL] placeholders the user needs to complete>
- <any tone concerns or facts that need verification>
- <one suggestion for follow-up after sending if relevant>

For PUBLIC channels (Google, Trustpilot, Facebook, Yelp), add a second block:

WHO ELSE READS THIS
===================
This reply is public. Future customers will see it. The reply must serve them too.
- Does the reply make the brand look reasonable to a stranger? <yes/no>
- Does it avoid escalating the complainant's framing? <yes/no>
- Does it offer a private path (DM, email, phone) for resolution? <yes/no - relevant for negative postures>

If any check is "no", flag it before showing the draft.

Phase 7 - Variants (optional)

After the first draft, ask:

Want a variant in a different posture or tone? (e.g. "shorter", "warmer", "more formal", "leave the upsell out", "more confident".)

If yes, generate one variant. Limit to 2 variants total - more than that is decision fatigue.

Failure modes to watch

• Defaulting to generic customer-service AI voice. Every reply must apply the operator or brand voice. A generic reply is worse than no reply for a brand customer.
• Defensive replies to negative reviews. Acknowledging the specific complaint is the move. Defending the brand publicly almost always reads badly to future readers.
• Inventing facts. If the user did not supply a price, return policy, or wait time, write [FILL: <description>] rather than guess.
• Wrong posture pick. Warm thank-you to a 3-star review reads tone-deaf. De-escalation to a happy customer reads insincere. Confirm the posture before drafting if unsure.
• Public reply written for the complainant only. Public replies are also read by every future customer who looks at the platform. Write for both audiences.
• Forgetting regulatory forbidden_claims. A brand with regulated language obligations must not relax in customer replies. Scan every draft against the forbidden_claims list.
• Length-creep. A DM reply that runs 200 words signals the brand cannot edit. Stay inside the channel's length budget unless the posture demands more (de-escalation can run longer).

Rules

• One question at a time during gathering.
• Never invent facts the operator did not supply.
• No money ask before permission. The Soft sell and Reactivation postures surface interest only (no price, deposit, pre-order, order, payment link, agreement to pay later, or date, slot, appointment or box held for them) unless the founder's files or this conversation show they may take money for this activity where they sell (a licence or permit that covers it). If they do not, ask once. Earlier sales to friends are not that permission.
• Voice rules apply to every draft, regardless of channel.
• If the incoming message asks something the brand legally cannot answer (medical advice, financial guarantees, etc.), surface that to the operator BEFORE drafting and offer a compliant alternative.
• If the customer attached a photo or screenshot the operator describes, acknowledge it specifically in the reply where it would land naturally.
• For multi-language brands: if the incoming message is not in English and a brand language is specified in positioning.yml, draft in that language. Otherwise ask the operator which language to reply in.