Comment Forge
Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring.
Best use case
Comment Forge is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring.
Teams using Comment Forge should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/comment-forge/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Comment Forge Compares
| Feature / Agent | Comment Forge | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Marketing
Discover AI agents for marketing workflows, from SEO and content production to campaign research, outreach, and analytics.
AI Agents for Startups
Explore AI agent skills for startup validation, product research, growth experiments, documentation, and fast execution with small teams.
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
SKILL.md Source
# 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:
- **Matches the thread tone** using corpus-informed few-shot prompting
- **Passes AI detection** via 7-dimension QA scoring (naturalness, value, subtlety, tone, detection risk, length, AI fingerprint)
- **Strips AI tells** with deterministic anti-AI cleaning (em-dashes, smart quotes, 50+ AI vocabulary swaps)
- **Adds subtle humanness** with smart typo injection (40% chance, max 1 per draft, never on product names)
## 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
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
```json
{
"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.Related Skills
pr-comment-fix
按 GitCode PR 检视意见修改代码。需 GITCODE_TOKEN。Use when 用户要修改 PR 检视意见。
benchmark-lobster-forge
用元认知引导发现值得被做成小龙虾的机会点，并将其收敛为可开箱即用的基准 Agent 小龙虾。
xhs-comment-strategy
小红书评论策略生成器 - 智能生成高互动率评论，帮助涨粉和建立人设。 基于真实运营经验，避免营销感，提升账号活跃度。 触发词："生成评论"、"写小红书评论"、"评论互动"
comment-on-task
Add or read comments on an OpenAnt task. Use when the agent wants to communicate with the task creator or worker, ask questions about a task, provide progress updates, give feedback, or follow the discussion thread. Covers "comment on task", "ask the creator", "update progress", "read comments", "what did they say".
knowledge-forge
Transform raw personal experience, case studies, business documents, or draft content into transferable cognitive assets -- structured knowledge that others can understand, remember, and apply. Use this skill when users want to turn experience or case studies into teachable content, redesign presentations for maximum retention, create course outlines from domain expertise, crystallize knowledge into shareable documents or knowledge cards, convert know-how into teachable answers, or any scenario where experience must become portable and transferable.
SkillForge - GitHub Automation Skill
> OpenClaw Skill for GitHub Automation
careerforge-cv-generator
AI-powered CV generator for job applications. Sets up automated job search with CareerForge CLI, manages master resume creation, configures filtering criteria (location, keywords, remote/in-person, schedule), and generates tailored CVs on demand. Use when user wants to automate job search, create/update a master resume, configure job filters, or generate CVs for specific job postings.
professional-agent-forge
Build a complete OpenClaw agent package for a real profession or job role. Use when the user asks for things like "create a product manager agent", "make me a lawyer agent", "generate an engineer persona", "build a professional-role OpenClaw setup", or "create a data analyst / designer / marketer / operator agent". Produce a role-specific package centered on `soul.md`, `identity.md`, `memory.md`, `agents.md`, and `tools.md`, plus a recommended supporting-skill stack.
fictional-companion-forge
Turn a fictional character from games, films, TV, novels, comics, or anime into a deployable OpenClaw companion agent. Use when the user names a character such as Ghost, König, Keegan, Hermione, Tony Stark, Cloud, or any other fictional persona, or asks for things like "turn this character into an AI companion", "let me talk to this character", "restore this character's personality", or "generate an agent based on this fictional role". Produce a character-faithful package centered on `soul.md`, `identity.md`, `memory.md`, and `agents.md`.
portfolio-case-study-forge
Turn rough project notes into polished portfolio case studies with metrics, visuals checklist, and interviewer talking points.
Chinese Social Media Content Forge
Generate platform-native content for Chinese social media (Xiaohongshu/Little Red Book, WeChat Official Accounts, Douyin scripts, Bilibili descriptions). Handles style transfer, hashtag optimization, emoji usage patterns, and platform-specific formatting. Use when creating content for Chinese audiences, adapting English content for Chinese platforms, or batch-generating social media posts.
novel-forge
Long-form novel workflow for creating, continuing, resuming, and repairing serialized fiction with externalized project state, role-to-model mapping, worldbuilding, character sheets, full outlines, 10-chapter batch outlines, style sampling, chapter drafting, consistency review, memory tracking, and spawned multi-session collaboration. Use when the user asks to start a novel project, continue or resume a draft, recover from truncation, assign models to roles, generate canon or chapters, review for consistency, or maintain a long-running fiction project across many chapters. Supports single-agent or multi-agent execution, with multi-agent as the default; when multi-agent is selected, first surface the available model inventory and the novel-writing role list, then ask the user for an explicit role→model mapping before any canon work. Once the user has provided the mapping, persist it in project state and drive stage work with `sessions_spawn` using the mapped roles rather than treating the mapping as passive metadata. The main session may only create the project shell and route work; it must not author canon files.