Reddit Icp Monitor

What it does

When your agent uses it

• Asked to monitor Reddit for ICP signals
• Find prospects on Reddit
• Surface pain point posts
• Draft helpful Reddit replies

Example prompts

• “monitor Reddit for my ICP”
• “find people on Reddit who need my product”
• “scan subreddits for pain points”
• “/reddit-icp-monitor”

Requirements

• Python 3
• A credential in GEMINI_API_KEY
• A credential in REDDIT_CLIENT_SECRET
• Compatibility (from SKILL.md): ["claude-code","gemini-cli","github-copilot"]

Workflow steps

7 steps, taken from the step headings in SKILL.md.

1. 1Setup Check
2. 2Load ICP
3. 3Search Reddit
4. 4Score Relevance with Gemini
5. 5Draft Replies with Gemini
6. 6Self-QA
7. 7Output and Save

What it can do on your machine

Read from SKILL.md and the folder at commit 62e437a. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • python3
  • curl

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • reddit.com
  • oauth.reddit.com
  • generativelanguage.googleapis.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • GEMINI_API_KEY
  • REDDIT_PASSWORD
  • REDDIT_CLIENT_SECRET

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  ["claude-code","gemini-cli","github-copilot"]

  From compatibility in the SKILL.md frontmatter.

Context cost

Reddit Icp Monitor loads about 2.7k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 143 tokens; SKILL.md has 782 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~143

When it runs · the whole SKILL.md, loaded when a task matches

~2.7k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NoteMentions a .env fileSKILL.md:29

  t at aistudio.google.com. Add it to your .env file."

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Varnan-Tech/opendirectory at commit 62e437a, republished under its MIT licence (© Varnan-Tech). 782 words, ~2,692 tokens.

name

reddit-icp-monitor

description

Watches subreddits for people describing the exact problem you solve, scores their relevance to your ICP, and drafts a helpful non-spammy reply for each high-signal post. Use when asked to monitor Reddit for ICP signals, find prospects on Reddit, surface pain point posts, draft helpful Reddit replies, or scan subreddits for buying signals. Trigger when a user says "monitor Reddit for my ICP", "find people on Reddit who need my product", "scan subreddits for pain points", "draft Reddit replies for prospects", or "check Reddit for buying signals".

compatibility

["claude-code","gemini-cli","github-copilot"]

author

OpenDirectory

version

1.0.0

echo "GEMINI_API_KEY: ${GEMINI_API_KEY:+set}"
echo "REDDIT_CLIENT_ID: ${REDDIT_CLIENT_ID:-not set, using public endpoints (10 RPM)}"

TOKEN=$(curl -s -X POST \
  -d "grant_type=password&username=$REDDIT_USERNAME&password=$REDDIT_PASSWORD" \
  --user "$REDDIT_CLIENT_ID:$REDDIT_CLIENT_SECRET" \
  -H "User-Agent: varnan-skills/1.0" \
  https://www.reddit.com/api/v1/access_token \
  | python3 -c "import sys,json; print(json.load(sys.stdin)['access_token'])")

ls docs/icp.md 2>/dev/null && echo "icp found" || echo "icp missing"

curl -s \
  -H "User-Agent: varnan-skills/1.0" \
  "https://www.reddit.com/r/{SUBREDDIT}/search.json?q={PHRASE}&sort=new&t=week&limit=25&restrict_sr=true" \
  | python3 -c "
import sys, json
d = json.load(sys.stdin)
posts = d.get('data', {}).get('children', [])
for p in posts:
    data = p['data']
    print(json.dumps({
        'id': data['id'],
        'title': data['title'],
        'body': data.get('selftext', '')[:600],
        'url': 'https://reddit.com' + data['permalink'],
        'score': data['score'],
        'comments': data['num_comments'],
        'subreddit': data['subreddit'],
        'created_utc': data['created_utc']
    }))
"

ENCODED=$(python3 -c "import urllib.parse, sys; print(urllib.parse.quote(sys.argv[1]))" "{PHRASE}")

cat > /tmp/reddit-score-request.json << 'ENDJSON'
{
  "system_instruction": {
    "parts": [{
      "text": "You are a GTM analyst identifying Reddit posts where someone is experiencing the exact pain point that a specific product solves. For each post provided, output a JSON object with these fields: id (the post id), score (integer 1-5), reason (one sentence explaining the score). Scoring rubric: 5 = person clearly has the problem AND is actively seeking help or venting frustration about it; 4 = strong signal, problem is present but less explicit; 3 = possible match, uncertain; 2 = tangentially related but not the core pain; 1 = unrelated. Output only a JSON array of score objects. No commentary before or after the array."
    }]
  },
  "contents": [{
    "parts": [{
      "text": "POSTS_AND_ICP_CONTEXT_HERE"
    }]
  }],
  "generationConfig": {
    "temperature": 0.2,
    "maxOutputTokens": 2048
  }
}
ENDJSON
curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d @/tmp/reddit-score-request.json \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['candidates'][0]['content']['parts'][0]['text'])"

cat > /tmp/reddit-reply-request.json << 'ENDJSON'
{
  "system_instruction": {
    "parts": [{
      "text": "You are a practitioner who has personally solved the exact problem being described in this Reddit post. Write a helpful reply that: (1) directly addresses what the person asked or is frustrated about, (2) shares a specific, useful insight from real experience, (3) does NOT mention any product, tool, or company by name unless the post explicitly asks for tool recommendations, (4) is 2-5 sentences, written in plain conversational prose with no headers or bullet lists, (5) optionally ends with a low-pressure invitation to continue the conversation. Do not use marketing language. Do not use these words: game-changer, best-in-class, streamline, transform, revolutionize, leverage, seamless, robust, comprehensive, innovative. Sound like a real person."
    }]
  },
  "contents": [{
    "parts": [{
      "text": "POST_CONTENT_AND_MODE_HERE"
    }]
  }],
  "generationConfig": {
    "temperature": 0.7,
    "maxOutputTokens": 512
  }
}
ENDJSON
curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d @/tmp/reddit-reply-request.json \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['candidates'][0]['content']['parts'][0]['text'])"

## Reddit ICP Monitor — [YYYY-MM-DD]

**Subreddits monitored:** r/[subreddit1], r/[subreddit2]
**Time window:** Last 7 days
**Keywords searched:** [phrase1], [phrase2], [phrase3]
**Candidates found:** X posts
**High-signal matches (score 4-5):** Y posts

---

### Match 1 — Score [N]/5
**Post:** [title](url)
**Subreddit:** r/[subreddit] | [N] upvotes | [N] comments
**Signal quote:** "[relevant excerpt from post body]"
**Matched keyword:** [phrase]
**Post type:** Mode [1/2/3]

**Drafted reply:**
[reply text]

**Reply word count:** N words

---

[repeat for each match]

---

**Subreddits with 0 results:** [list any that returned nothing]

mkdir -p docs/reddit-intel
OUTFILE="docs/reddit-intel/$(date +%Y-%m-%d).md"
cat > "$OUTFILE" << 'EOF'
REPORT_CONTENT_HERE
EOF
echo "Saved to $OUTFILE"

© Varnan-Tech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/reddit-icp-monitor of Varnan-Tech/opendirectory.

• SKILL.md
• .env.example
• README.md
• evals/evals.json
• references/icp-format.md
• references/reply-rules.md

Open the folder on GitHubat commit 62e437a