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FactoriaGo

v2.9.7

FactoriaGo platform assistant — AI-driven academic paper revision and resubmission. Activate when user mentions: FactoriaGo, revise paper, reviewer comments,...

0· 157·0 当前·0 累计
by @gyh2556406 (Ge Yanhao)·MIT-0
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License
MIT-0
最后更新
2026/4/14
安全扫描
VirusTotal
可疑
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OpenClaw
可疑
medium confidence
The skill's code and instructions largely match its stated purpose (FactoriaGo paper revision), but there are a few inconsistencies around environment variable declarations and handling of credentials that you should understand before installing.
评估建议
What to consider before installing/using this skill: - The skill appears to do what it says: it calls the FactoriaGo API (editor.factoriago.com) to manage projects, files, review analysis, AI chat, and LaTeX compile. - Inconsistency to note: the registry reported no required environment variables, but the included client script expects a session cookie in FACTORIAGO_COOKIE. Expect to set that env var or login via the script. - Sensitive credentials: to use AI features you must provide an LLM API...
详细分析 ▾
用途与能力
Name/description (FactoriaGo paper revision, LaTeX editing, reviewer-response drafting) align with the included files and the client script: the script talks only to editor.factoriago.com and implements project, task, file, chat, and LLM config endpoints consistent with the documentation.
指令范围
SKILL.md and the included docs instruct the agent and user to perform login, manage a session cookie, call /api endpoints, upload LLM API keys to the platform, analyze reviews, edit files, and compile LaTeX. These instructions stay within the stated purpose. Minor mismatch: some docs use factoriago.com vs editor.factoriago.com for endpoints (script uses editor.factoriago.com). The skill explicitly instructs the agent to ask for credentials before API calls and to store the session cookie in an env var rather than in files.
安装机制
Instruction-only skill with a bundled client script; there is no install spec, no downloads, and nothing writes to disk beyond what the user runs locally. This is a low-risk installation model from a delivery standpoint.
凭证需求
Registry metadata lists no required env vars or primary credential, but the bundled script expects the session cookie in FACTORIAGO_COOKIE (and the SKILL.md instructs users to export that env var). Additionally, AI features require you to provide your own LLM API key which the skill instructs you to send to the FactoriaGo server via set-llm-config (server-side storage). Requesting a session cookie and API keys is proportionate to the functionality, but the env var requirement was not declared in the registry and the skill instructs the user to upload sensitive credentials to the remote service—this requires trusting the remote platform and the skill author.
持久化与权限
The skill is not always-enabled and does not request system-wide persistence or modify other skills. It does instruct storing a session cookie in an environment variable for the duration of use, which is normal for a client script.
安全有层次,运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发,无需署名。

运行时依赖

无特殊依赖

版本

latestv2.9.72026/3/18

Re-publish with Apache 2.0 license and full English documentation

● 可疑

安装命令 点击复制

官方npx clawhub@latest install factoriago
镜像加速npx clawhub@latest install factoriago --registry https://cn.clawhub-mirror.com

技能文档

FactoriaGo (factoriago.com) is an AI-native LaTeX editor built for academic paper revision. Core value: turn reviewer feedback into a structured revision plan, then revise in-browser.

🔒 Security Note

This skill makes network requests only to editor.factoriago.com (the official FactoriaGo platform) and your chosen AI provider (e.g., Anthropic, OpenAI). No data is sent to any third-party or unknown endpoints. The CLI script (scripts/factoriago-client.js) handles:

  • Session authentication via HTTPS cookie
  • API calls to https://editor.factoriago.com/api/*
  • LLM API key configuration (keys are encrypted server-side)

The VirusTotal warning is a false positive triggered by the presence of external API calls and credential-handling patterns, which are inherent to any API integration skill.

Quick Reference

  • Product URL: https://factoriago.com
  • Landing page: https://factoriago.com
  • App & API base: https://editor.factoriago.com/api
  • API docs: See references/api.md
  • Revision workflow: See references/revision-workflow.md
  • Reviewer response templates: See references/reviewer-response.md
  • CLI client: scripts/factoriago-client.js

⚠️ Prerequisites: LLM API Key Setup

AI features (chat, review analysis, revision suggestions) require a personal LLM API key. Without it, users can only edit files and compile LaTeX — no AI assistance.

Always check API key status before attempting AI operations:

node scripts/factoriago-client.js get-llm-config

If primary_key_saved: false, guide the user through setup FIRST:

API Key Setup Flow

  • Ask which AI provider they want:
- Anthropic → Claude 3.5 Sonnet (best for writing) - OpenAI → GPT-4o (general purpose) - Google → Gemini 2.0 Flash (fast) - Moonshot → Kimi (Chinese papers) - Zhipu → GLM-4 (Chinese papers) - MiniMax → MiniMax (Chinese papers)

  • Tell them where to get the key:
| Provider | Key URL | |----------|---------| | Anthropic | https://console.anthropic.com/keys | | OpenAI | https://platform.openai.com/api-keys | | Google | https://aistudio.google.com/app/apikey | | Moonshot (Kimi) | https://platform.moonshot.cn/console/api-keys | | Zhipu (GLM) | https://open.bigmodel.cn/usercenter/apikeys | | MiniMax | https://platform.minimaxi.com/user-center/basic-information/interface-key |

  • Save the key via API:
   node scripts/factoriago-client.js set-llm-config   
   
Or guide user to: Settings → AI Model in the FactoriaGo web UI.

  • Confirm key is saved before proceeding with AI tasks.
API keys are encrypted server-side and never exposed in plaintext after saving.

Workflows

1. New User Onboarding

When user is new to FactoriaGo:

  • Explain what FactoriaGo does (revise & resubmit workflow, AI co-author, LaTeX editor)
  • Direct to https://factoriago.com to register (free tier available)
  • Key differentiators to highlight:
- Bring Your Own AI Model (Claude, GPT-4o, Gemini, Kimi, GLM — use own API keys) - Browser-based LaTeX editing + compilation (no local install needed) - Real-time collaboration + reviewer comment management - 12 languages supported

2. API Integration

Always check API key first before AI operations (see Prerequisites above).

Auth setup:

# Login and get session cookie
export FACTORIAGO_COOKIE=$(node scripts/factoriago-client.js login   | grep "Cookie:" | cut -d' ' -f2-)

Common commands:

node scripts/factoriago-client.js list-projects
node scripts/factoriago-client.js list-tasks 
node scripts/factoriago-client.js analyze-review  ""
node scripts/factoriago-client.js chat  "" [model]
node scripts/factoriago-client.js compile 

Always ask user for credentials before making API calls. Store cookie in env, never in files.

3. Reviewer Comment Analysis

When user pastes reviewer comments:

  • Read references/revision-workflow.md for the full workflow
  • Parse comments into individual concerns
  • Categorize: Major / Minor / Optional
  • Map each concern to a revision task
  • Suggest priority order (major methodological issues first)
  • Optionally call POST /paper/:id/analyze if user is logged in

4. Reviewer Response Letter

When user needs to write a response letter:

  • Read references/reviewer-response.md for templates and tone guidelines
  • For each reviewer comment:
- Determine user's position (agree / partially agree / disagree) - Draft response using appropriate tone template - Cite specific manuscript changes with section/line references
  • Assemble into full point-by-point letter
  • Use the AI prompt template in reviewer-response.md for AI-assisted drafting

5. LaTeX Editing

When user wants to edit manuscript:

  • get-file to read current content
  • Make targeted edits based on revision tasks
  • PUT /paper/:paperId/files/:fileId to save
  • compile to verify no LaTeX errors
  • Report compilation result to user

Key Facts for Onboarding

  • Free tier: available, limited AI quota
  • Paid plans: more AI calls, larger storage, priority compilation
  • Target users: researchers, PhD students, postdocs doing journal revisions
  • Supported formats: .tex, .bib, .zip (full LaTeX project)
  • No installation needed: fully browser-based
  • Supported AI models: Claude 3.5 Sonnet, GPT-4o, Gemini 2.0 Flash, Kimi, GLM-4, MiniMax
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