Comment Forge

---

name: Comment Forge

slug: comment-forge

version: 1.0.0

description: Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring.

author: OpenClaw

license: MIT

tags:

- reddit

- comments

- ai-detection

- content

- marketing

- copywriting

requires:

- python>=3.10

---

# Comment Forge

Generate Reddit-native comments that sound like a real person wrote them. Powered by a real Reddit comment corpus and a 7-dimension QA pipeline that catches AI fingerprints.

What It Does

Feed it a post title, body, and existing comments. Get back a natural reply that:

Two Modes

**Value-First**: Pure tactical advice. No product mention. Great for building karma and credibility.

**Product-Drop**: Mention a product naturally in the reply. Auto-fit scoring determines if the product fits the thread (1-10 score). If it doesn't fit naturally, falls back to value-first.

Pipeline

1. **Corpus Sampling** - Stratified, score-weighted real Reddit comment examples

2. **Fit Scoring** - Classify thread intent, recommend mode (optional, for product-drop)

3. **Draft Generation** - Corpus-informed few-shot prompting via Gemini or OpenRouter

4. **QA Pipeline** - Score, revise, re-score loop (3 attempts for product-drop, 7 for value-first)

5. **Anti-AI Cleaning** - Deterministic post-processing strips AI vocabulary, em-dashes, smart quotes

6. **Human Touch** - Smart typo injection for believable imperfections

Quick Start

bash setup.sh
source .venv/bin/activate

# Value-first (no product)
python3 comment_forge.py --post "Best CRM for small teams?"

# Product-drop
python3 comment_forge.py --post "What tools do you use for email?" \
  --product "Acme Mail" --product-desc "Email automation for small teams"

# With existing comments for tone matching
python3 comment_forge.py --post "How do you handle cold outreach?" \
  --comments "I use Apollo" "LinkedIn works best imo"

# From JSON file
python3 comment_forge.py --file post.json --json

# Skip QA (faster)
python3 comment_forge.py --post "..." --skip-qa

JSON File Format

{
  "title": "Best CRM for small teams?",
  "body": "Looking for something simple...",
  "comments": [
    "I use HubSpot free tier",
    "Notion works if you're small"
  ],
  "product": "Acme CRM",
  "product_url": "https://acme.com",
  "product_description": "Simple CRM for small teams",
  "category": "saas",
  "mode": "product_drop"
}

API Keys

| Key | Required | Purpose |

|-----|----------|---------|

| `GEMINI_API_KEY` | Yes (or OpenRouter) | Primary LLM for generation + QA |

| `OPENROUTER_API_KEY` | Fallback | Alternative LLM provider |

| `CEREBRAS_API_KEY` | Optional | Fast fit scoring (free tier) |

QA Dimensions

| Dimension | Weight | What It Checks |

|-----------|--------|----------------|

| naturalness | 15% | Does it sound like a real person? |

| value_contribution | 15% | Does it help the thread? |

| subtlety | 20% | Is the product mention (if any) natural? |

| tone_match | 10% | Does it match thread + corpus tone? |

| detection_risk | 10% | Would redditors flag it as spam? |

| length_appropriate | 10% | Right length for this thread type? |

| ai_fingerprint | 20% | Em-dashes, AI vocab, perfect grammar? |

Pass threshold: 7.0/10 composite score.