Kai reddit listen

Kai root note: knowledge/, harness/, and scripts/ paths in this skill live in the Kai install, not the user's project. Resolve them against the first ancestor directory of this SKILL.md that contains a knowledge/ folder (the Kai plugin root, ~/.claude/kai, or the kai-cmo-harness repo). MARKETING.md, memory/, and any output files live in the current project. If a referenced scripts/ command is not available in this install, say so, skip it, and continue with the file-based guidance — never fabricate its output.

Build and run a profile-driven Reddit listener. Engine lives at scripts/reddit_monitor/; each brand/client is a profile (subreddits + trigger keywords + LLM prompt + Discord webhook).

When to use

• Founder/operator wants inbound leads from subreddit conversations
• Product has a specific technical wedge (useful insights → honest replies)
• You already tried manually scanning Reddit and it doesn't scale
• Brand voice + identity rules matter (don't fake experience you don't have)

When NOT to use

• Post volume in target subs is low (<5/day total) — keyword filter will starve
• Brand has no distinctive angle — generic replies get auto-removed by Reddit
• You need engagement metrics (this only drafts replies, doesn't track results)

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Phase 0: Load Product Context

Check if MARKETING.md exists in the project root. If present, read it for ICP, voice, pain points, and product positioning — these drive subreddit/keyword/prompt choices. If absent, run /kai-start first or ask the user for: product, ICP, voice rules, what they can/can't honestly claim as expertise.

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Phase 1: Profile Discovery

A "profile" = one JSON config + one prompt file at scripts/reddit_monitor/profiles/<name>.{json,prompt.md}.

1. Does a profile exist for this brand/client?

   • List scripts/reddit_monitor/profiles/*.json
   • If yes → --dry-run it (Phase 5) before changing anything
   • If no → go to Phase 2

2. What's the goal?

   • (a) Find posts where we can honestly add technical value → builder identity
   • (b) Find pain-point posts in vertical subs → client-learning identity
   • (c) Find comparison/recommendation threads → share stack

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Phase 2: Configure Subreddits

Pick subs in three tiers. Aim for 15-30 total — more than 30 and RSS pulls get slow.

Tier	Purpose	Examples
Primary	Direct category matches	r/AIReceptionists for voice AI; r/RemoteWork for remote tools
Adjacent	Where ICP hangs out	r/SaaS, r/startups, r/gtmengineering
Vertical	Target customer verticals	r/LawFirm, r/HVAC, r/smallbusiness

Rules:

• Use exact sub name, no r/ prefix
• Test each in a browser first — some subs are private or dead
• Vertical subs often have stricter anti-promo rules → identity guardrails in the prompt matter more here

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Phase 3: Configure Trigger Keywords

Keywords are the pre-filter before the LLM eval (cheap string match on title+body). Design them to cast a wide net; the LLM rejects the garbage.

Four buckets:

1. Category terms — exact product category ("voice ai", "ai receptionist")
2. Competitor names — ("vapi", "twilio", "retell")
3. Technical jargon — things only buyers/builders say ("latency", "transcription", "vad")
4. Pain-point phrases — how the problem is described ("missed calls", "after hours", "speed to lead")

Rules:

• Lowercase (match is case-insensitive)
• Multi-word phrases OK and preferred ("voice ai" > "voice")
• Avoid single generic words ("marketing", "sales") — too noisy
• 20-40 keywords is the sweet spot

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Phase 4: Write the LLM Prompt

This is where brand voice and identity guardrails live. The prompt file uses Python .format() placeholders — {subreddit}, {title}, {content} — and must instruct the model to return JSON with pass (bool), reason (str), angle (str|null), draft_response (str|null).

Copy profiles/example.prompt.md as the starting point. Then fill in:

Identity section (critical)

• "You ARE X (honestly claim)"
• "You are NOT Y (don't fake)"
• "You have LEARNED Z from building for clients" (bridge claim)

Reject/Accept rules

• REJECT triggers that would require fabricating experience
• REJECT off-topic, job posts, career advice
• ACCEPT posts where genuine technical value is addable

Voice rules

• Tone (casual/formal), case (lowercase/sentence case), openers, forbidden words
• Example of good reply, example of bad reply (generic, cheerleader-y, faked experience)

Insight bank

• 3-8 specific, repeatable insights the model can draw from
• One-liner per insight (latency numbers, % stats, architectural tips)

Closing

• Literal JSON only: instruction with the 4-key schema

Keep the JSON example at the bottom {{ }}-escaped so .format() doesn't try to substitute it.

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Phase 5: Test Dry-Run

Set the profile's webhook env var is not required in dry-run mode.

cd scripts/reddit_monitor
python reddit_listener.py --profile <name> --dry-run

Expect:

• "found N keyword matches" (N > 0 unless you just ran it — seen-posts dedup)
• Per-post pass/reject decisions
• Drafts printed to stdout for each pass

Red flags:

• Every post rejects → identity rules too strict, or keywords too narrow (pulling off-topic)
• Every post passes → identity rules too loose, not rejecting job posts/off-topic
• Drafts sound generic → insight bank too thin or voice rules too weak
• Drafts fake experience → identity section wasn't explicit enough

Iterate prompt → re-run dry-run. Don't ship until drafts would plausibly pass in the actual sub.

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Phase 6: Go Live + Automate

1. Set the Discord webhook env var named by the profile (e.g. REDDIT_MONITOR_DISCORD_WEBHOOK_KAICALLS). Create a dedicated channel with a channel-specific webhook — don't reuse a shared one.

2. Local cron (Windows Task Scheduler / macOS launchd / Linux cron):

   # daily at 12:00
   0 12 * * * cd /path/to/scripts/reddit_monitor && python reddit_listener.py --profile <name> >> /var/log/reddit-<name>.log 2>&1
   

3. Hermes cron (original KaiCalls setup): same pattern at /opt/cmo-analytics/reddit-monitor/ — the original env relied on OPENAI_API_KEY which is not in hermes env today (last-successful-run evidence: seen_posts.json stopped updating 2026-02-21). Fix by adding OPENAI_API_KEY to hermes env, or swap OpenAI() → OpenRouter via OpenAI(base_url="https://openrouter.ai/api/v1", api_key=os.environ["OPENROUTER_API_KEY"]).

4. First-week monitoring: eyeball every Discord alert. Kill the cron and go back to Phase 4 if drafts are off. Don't let bad drafts run unsupervised.

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Profile Schema

Key	Required	Default	Purpose
subreddits	yes	—	list of sub names (without r/)
trigger_keywords	yes	—	case-insensitive substrings for pre-filter
prompt_file	yes	—	filename in profiles/; .format()'d with {subreddit}, {title}, {content}
discord_webhook_env	yes	—	env var name holding the Discord webhook URL
name	no	filename stem	used for state filename and logging
alert_title	no	Reddit Opportunity	shown in Discord alert header
model	no	gpt-4o-mini	OpenAI model id
seen_limit	no	2000	ring-buffer size for seen post IDs
posts_per_sub	no	25	max posts pulled per sub per run
content_max_chars	no	1200	post body truncation before LLM

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Engine Location

• Script: scripts/reddit_monitor/reddit_listener.py
• Runner (cron wrapper, emits ALERTS_JSON: line): scripts/reddit_monitor/run_listener.sh <profile>
• Profiles: scripts/reddit_monitor/profiles/
• State (per-profile, gitignored): scripts/reddit_monitor/.seen/<name>.json
• Docs: scripts/reddit_monitor/README.md

Required env

• OPENAI_API_KEY — LLM eval (reads from repo-root .env, parent, or sibling)
• <discord_webhook_env> — per profile

When to compose with other skills

• After drafts arrive in Discord and you want to polish before posting → /kai-write or /kai-gate (check against banned words, Four U's)
• To identify subs + keywords you didn't know about → /kai-competitors (reverse-engineer where competitors are active)
• If drafts are generic → /kai-brand to tighten voice rules before rewriting the prompt