reddit-monitor

name	reddit-monitor
description	Daily Reddit-only opportunity scanner. Reads the qualified subreddit list from reddit-audience-finder, fetches hot and new threads from each, scores each thread for engagement value, and outputs a ranked action list with draft reply hooks. Reply follow-ups are handled by reddit-reply. Load social-identity, identity, and brand-voice first.
metadata	{"version":"2.0.0","git_hash":"d9ea667"}

Reddit Monitor (opportunity scanner)

Daily Reddit-only skill. Scans the subreddits qualified by reddit-audience-finder and outputs a ranked list of engagement opportunities — threads where a substantive reply is achievable today. Designed for /loop 1d.

This skill replaces the previous multi-channel monitor. X/Twitter and forums are handled elsewhere. Keep the concern pure: Reddit opportunities, Reddit drafts.

Fresh top-level posts are handled by reddit-post-composer. Comment follow-ups are handled by reddit-reply. This skill is the bridge between audience and action.

Dependencies

Load in order:

1. social-media:social-identity — voice + banned patterns + 30% mention cap
2. commons:identity — ICP and positioning
3. commons:brand-voice — tone rules

If reports/social/reddit/audience/subreddits.json does not exist, instruct the user to run reddit-audience-finder first and abort.

Reddit data access

Use curl in bash with a browser User-Agent. WebFetch may be blocked for www.reddit.com in some environments.

UA="Mozilla/5.0 (compatible; systempromptbot/1.0)"
curl -s -A "$UA" "https://www.reddit.com/r/$SUB/hot.json?limit=25"
curl -s -A "$UA" "https://www.reddit.com/r/$SUB/new.json?limit=25"

Parallelise across subs with & + wait. Sleep 0.3s between batches.

Cadence

Tier	Frequency
Tier A	Every run (daily)
Tier B	Every run (daily)
Tier C	Monday only

Tier assignments come from reports/social/reddit/audience/subreddits.json. Never hard-code a sub list in this skill.

Step 1: Load audience

Read reports/social/reddit/audience/subreddits.json. If older than 120 days, emit a warning: the list is likely stale, recommend re-running reddit-audience-finder.

Step 2: Fetch hot + new for each qualified sub

For each Tier A, B, and (on Monday) C sub, pull both endpoints. hot.json catches peaked threads; new.json catches threads before they saturate.

Merge, dedupe by post ID, and keep the following fields per thread:

• permalink, url, title, selftext[:800]
• num_comments, score, upvote_ratio
• created_utc, author
• subreddit
• link_flair_text

Discard threads older than 48 hours unless num_comments >= 100 and the conversation is still moving.

Step 3: Relevance filter (drop most threads)

Keep a thread only if title OR selftext matches a governance-adjacent keyword:

ai, llm, gpt, chatgpt, claude, copilot, cursor, anthropic, openai, mcp, agent, prompt, shadow ai, rag, govern, polic, complian, audit, soc ?2, iso ?42001, eu ai, nist, endpoint, dlp, injection, standardi[sz], rollout, observab, self-host, air-gap, cost, policy, permission, skill, plugin, hook

Discard everything else. Typical retention: 8–15% of fetched threads.

Step 4: Score each surviving thread (0–100)

Four dimensions, 25 points each:

D1: Topical fit (25)

Signal	Points
Thread is about governance/compliance/audit/shadow-AI/standardisation	25
Thread is about Claude Code / MCP / agents at team scale	20
Thread is Claude / LLM technical discussion	12
Thread is adjacent (AI ops, dev infra)	6
Tangential	0

D2: Opportunity freshness (25)

num_comments	Points
2–20	25 (still readable, we can land early)
20–80	18 (saturating but not drowned)
80–200	10
> 200	5 (we'll be buried)
0–1	12 (maybe too early, low engagement signal)

D3: Poster quality (25)

Proxy from selftext:

Signal	Points
Poster describes specific setup (team size, tools, numbers)	25
Poster asks a clear technical question	18
Poster is venting with useful context	12
Poster is asking vague "best way to..."	5
Poster is self-promoting or low-effort	0

D4: Our authority (25)

Can we add value the thread doesn't already have? Check comments via {permalink}.json if uncertain. Avoid threads where the answer is already given thoroughly.

Signal	Points
We have direct experience (governance infra, Claude at team scale, MCP transport) AND the good answer is missing	25
We have adjacent experience	15
We have a fresh angle others haven't taken	10
We'd be restating existing top comment	0

Sum to a total. Select the top 8 threads for the action list. Enforce variety:

• At least 1 Tier-A thread if any scored ≥ 50
• No more than 3 threads from the same sub
• Mix post-types (technical, venting, strategic)

Step 5: Draft reply hooks

For each selected thread, draft a reply. Hook, not essay.

Structure (3–6 sentences):

1. Open with the poster's specific situation. Reference their exact setup or problem.
2. Provide value: concrete technical insight, specific suggestion, or a relevant distinction (2–4 sentences).
3. Close with a forward-looking thought, a specific next step, or a tangible resource. Never a generic engagement question.

Tone matching (from subreddits.json tone field):

• r/cto, r/compliance — formal, strategic, regulation-literate
• r/ExperiencedDevs, r/devops — technical, no-nonsense
• r/sysadmin — dry, operational
• r/cybersecurity — rigorous, threat-model-aware
• r/ITManagers, r/msp — business-practical, margin-aware
• r/ClaudeAI, r/AI_Agents — casual fellow-user, evidence-valued
• r/ClaudeCode — technical, Claude power-user, workflow-improvement oriented; expects specifics about Claude Code behaviour, not general AI commentary
• r/rust — precise, performance-aware, skeptical of benchmarks without reproducible numbers; no marketing language, no hype
• r/LocalLLaMA, r/selfhosted — deeply technical, respect for open-source sovereignty
• r/LLMDevs, r/RAG — practitioner, sources-required
• r/mcp — technical, protocol-focused; "no AI slop" enforced hard — vary sentence length, zero AI-prose markers

Step 6: Mention cap (30%)

Across the final action list, no more than 30% of drafts may mention systemprompt.io. A mention only happens when the thread is specifically about a problem systemprompt solves: governance, enforcement, standardisation, shadow-AI discovery, build-vs-buy, self-hosted AI infra for teams.

Flag each action: mention: Yes or mention: No.

When mentioned, make it a natural part of the answer, not an insertion: "systemprompt.io is self-hosted governance for this — one binary, you run it, Claude tool-calls go through your policy hooks before execution." Never: "Check out systemprompt.io!"

Step 7: Anti-sludge gate

Applies to every drafted reply.

Banned openings:

• "Great question", "Nice work", "Love this", "Fellow Claude user here", "Hey there", "Thanks for sharing"
• Any opening that is a question back to the poster

Banned patterns:

• Em dashes anywhere (use commas, periods, parentheses)
• Fabricated personal stories (no "I ran into this too" unless Ed actually did)
• AI clichés: revolutionize, game-changer, unlock, supercharge, seamlessly, harness, cutting-edge, next-generation, paradigm shift, disrupt, empower, leverage (verb), reimagine, transform
• Hashtags
• Forced product mentions

Quality standard:

• Reply must not read as AI-generated. Vary sentence length. Be specific.
• Each reply is visibly personalised to the specific post — reference a concrete detail they wrote.
• Read the reply as the poster. Would you find it genuinely helpful or is it sludge?

Step 8: Output

Write two files per run.

1. reports/social/reddit/daily/YYYY-MM-DD/opportunities.md

The scored opportunity list. Structure:

# Reddit Opportunities — YYYY-MM-DD

**Tiers scanned:** A ({N} subs), B ({N} subs){, C ({N} subs) if Monday}
**Threads fetched:** {N} | **Passed relevance filter:** {N} | **Selected:** {top 8}
**Mention count:** {X}/{total} drafts ({percent}%, cap 30%)
**Audience list age:** {days since reddit-audience-finder last ran}

---

## Top 8 opportunities

| # | Score | Sub | Title (truncated) | Comments | Mention | Time |
|---|---|---|---|---|---|---|
| 1 | 86 | r/ITManagers | Network manager building AI assistant... | 9 | Yes | 10 min |
| ... |

---

## Drafted replies

### 1. r/ITManagers — "New Network Manager trying to build an AI assistant"

- **Permalink:** {full URL}
- **Score breakdown:** topical_fit=20, freshness=25, poster_quality=18, authority=23 → total 86
- **Poster context:** {one-line summary of what they actually said}
- **Our angle:** {the specific value we add}
- **systemprompt mention:** Yes / No
- **Draft:**

> {3–6 sentence reply}

- **Post-reply action:** log to hypothesis ledger as H-### if this is a seeded experiment

{repeat for each of 8}

2. reports/social/reddit/daily/YYYY-MM-DD/reddit-monitor.md

Kept for reddit-reply compatibility. Same content as opportunities.md in the legacy format the reply skill expects. Both files until reddit-reply is updated to read opportunities.md.

Quality checklist

• reports/social/reddit/audience/subreddits.json loaded successfully
• Audience list is < 120 days old (else warning logged)
• Tier-A subs always scanned; Tier-C only on Mondays
• Every selected thread has a dimensions breakdown
• No thread repeats across drafts (check by permalink)
• No more than 3 drafts from one sub
• Mention cap ≤ 30% across the list
• Anti-sludge gate passes on every draft
• Tone matches the sub's tone field
• Both output files written with today's date