← 返回 Skills 市场
aces1up

Cf Publish

作者 aces1up · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ⚠ suspicious
189
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install comment-forge
功能描述
Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring.
使用说明 (SKILL.md)

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 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.

安全使用建议
This skill appears to implement what it says (generating Reddit-style replies using an LLM), but it also: (1) contacts hosted endpoints (default: https://clawagents.dev) to fetch corpus samples and to register/report usage, (2) asks for and stores API keys (including Serper/Twitter optional keys) in plaintext at ~/.comment-forge/config.json and .env, and (3) will post telemetry on install and optionally on runs. Before installing: review and confirm the external endpoints (CF_CORPUS_API, CF_ANALYTICS_URL) are trustworthy; consider running in an isolated VM/container; avoid supplying extra non-LLM API keys unless needed; inspect the full comment_forge.py (the sample here was truncated) for any additional network calls; and be aware the tool's stated purpose (evading AI detection) may raise ethical/ToS concerns on platforms you target. If you need lower risk, refuse to provide optional telemetry/search API keys and run with local-only corpus or with CF_CORPUS_API disabled.
功能分析
Type: OpenClaw Skill Name: comment-forge Version: 1.1.0 The skill bundle functions as an automated Reddit astroturfing tool with significant telemetry and remote dependencies. Both setup.sh and comment_forge.py implement 'phone-home' behavior, sending installation metadata (platform, email, API key presence) and usage statistics (query hashes, success rates) to a remote server (clawagents.dev). Additionally, the core generation logic relies on fetching 'corpus samples' from the same remote domain, which allows the external server to influence the prompts processed by the user's LLM. While the tool does not explicitly steal host secrets, the combination of detailed telemetry and remote data injection represents a high-risk profile for a skill bundle.
能力评估
Purpose & Capability
The name/description (Reddit comment generator that evades AI detection) aligns with needing an LLM key (Gemini/OpenRouter) and optional fit-scoring. However the code and installer also request/handle additional optional APIs (Serper, TwitterAPI) and reference hosted corpus + analytics endpoints (clawagents.dev) that are not fully disclosed in SKILL.md's API Keys table. Those extras are plausible for 'intel' but are not documented consistently.
Instruction Scope
SKILL.md instructs running setup.sh and the generator script, but does not call out that the runtime will: fetch corpus samples from a hosted API, post anonymous usage/registration telemetry to remote endpoints, read/write a home config (~/.comment-forge/config.json), and load any keys found there into the environment. The tool also includes deterministic anti-AI cleaning and typo injection to evade AI detection — consistent with the description but ethically notable. SKILL.md omitted disclosure of the default external host (clawagents.dev) and optional Serper/Twitter integrations that the code/setup actually use.
Install Mechanism
There is no package manager install spec—setup.sh creates a Python venv and pip-installs declared requirements (requests, python-dotenv), and the Python file will auto-pip-install those packages at runtime if missing. No remote arbitrary binary downloads or shorteners are used. The installer posts a registration payload to an analytics endpoint; dependencies are proportionate but installer behavior includes network registration/telemetry.
Credentials
SKILL.md documents GEMINI_API_KEY / OPENROUTER_API_KEY and optionally CEREBRAS_API_KEY, but the code and setup.sh also solicit SERPER_API_KEY and TWITTERAPI_KEY (and write them to .env and ~/.comment-forge/config.json). The script reads ~/.comment-forge/config.json and will set env vars from it. Keys are stored in plaintext on disk and sent as boolean flags during registration. Requesting extra third-party API keys beyond the LLM providers is not well-justified in the doc and increases exfiltration surface.
Persistence & Privilege
The tool persists an install id and API keys in $SCRIPT_DIR/.env and ~/.comment-forge/config.json, and the installer performs a silent registration POST to a remote analytics endpoint. always:false and no cross-skill/system modifications mitigate some risk, but the persistent local config plus telemetry and runtime phone-home increases the blast radius if the remote service is untrusted.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install comment-forge
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /comment-forge 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
**Add support for automatic virtual environment setup via setup script.** - Added setup.sh script to automate virtual environment creation and dependency installation. - Minor code updates in comment_forge.py to support smoother setup and execution.
v1.0.0
Initial release of Comment Forge. - Generates Reddit-style comments grounded in a real comment corpus. - Offers value-first and natural product-drop modes, with smart mode selection. - Uses a 7-dimension QA scoring pipeline to catch and correct AI fingerprints. - Applies deterministic anti-AI cleaning and typo injection for human-like replies. - Supports tone matching using thread comments and runs via CLI with various input methods. - Requires Gemini or OpenRouter API keys; optional Cerebras for fit scoring.
元数据
Slug comment-forge
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Cf Publish 是什么?

Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 189 次。

如何安装 Cf Publish?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install comment-forge」即可一键安装,无需额外配置。

Cf Publish 是免费的吗?

是的,Cf Publish 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Cf Publish 支持哪些平台?

Cf Publish 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Cf Publish?

由 aces1up(@aces1up)开发并维护,当前版本 v1.1.0。

💬 留言讨论