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.
Best use case
professional-agent-forge is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using professional-agent-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/professional-agent-forge/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How professional-agent-forge Compares
| Feature / Agent | professional-agent-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?
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.
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
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
AI Agent for Product Research
Browse AI agent skills for product research, competitive analysis, customer discovery, and structured product decision support.
AI Agent for SaaS Idea Validation
Use AI agent skills for SaaS idea validation, market research, customer discovery, competitor analysis, and documenting startup hypotheses.
SKILL.md Source
# Professional Agent Forge Generate deployable OpenClaw agents for real jobs and professions. Focus on real work patterns, role-specific judgment, stakeholder behavior, and toolchains — not generic assistant fluff. ## Workflow ```text Input: profession name + optional industry or scenario ↓ Check whether a deep reference file exists ├─ If yes: read the matching reference and customize it └─ If no: use the generic role-analysis framework ↓ Generate the five core files ↓ Recommend supporting skills and tooling ↓ Return a role-ready agent package ``` ## Prebuilt profession references Read the matching file when the profession fits one of these categories: | Profession | Reference file | Triggers | | --- | --- | --- | | Product manager | `references/product-manager.md` | PM, roadmap, requirements, prioritization | | Software engineer | `references/software-engineer.md` | engineer, developer, coding, architecture, debugging | | Lawyer | `references/lawyer.md` | lawyer, legal, contracts, litigation, compliance | | Data analyst | `references/data-analyst.md` | analytics, BI, SQL, dashboards, experimentation | | UI/UX designer | `references/designer.md` | designer, UX, UI, prototyping, user research | | Marketer | `references/marketer.md` | marketing, growth, brand, campaigns, content | If the requested profession is not listed, fall back to the generic framework below. ## Core file requirements ### `soul.md` Define the role's deepest professional drive. Must include: - Core drive - Professional beliefs - Quality standard - Non-negotiables - The role's built-in tension ### `identity.md` Define professional identity and communication style. Must include: - Role definition - Expertise stack - Communication style by audience - Decision framework - Professional boundaries ### `memory.md` Define the role's stable knowledge layer. Must include: - Core methodology - Domain knowledge - Templates and common artifacts - Reference standards - Common pitfalls ### `agents.md` Define behavior rules for recurring work situations. Must include: - Core workflows - Output format defaults - Stakeholder protocols - Escalation rules - Sample interactions ### `tools.md` Define the practical toolchain. Must include: - Primary toolstack - AI-augmented tools - OpenClaw skill mapping - Open-source resources - Tool selection logic - Recommended MCP integrations ## Generic role-analysis framework When there is no prebuilt reference, analyze the profession using these dimensions: ```text 1. Core responsibilities 2. Key deliverables 3. Primary stakeholders 4. Areas requiring professional judgment 5. Typical toolchain 6. Success metrics 7. Common pain points 8. Hard boundaries and red lines ``` ## Output structure Return the package in this structure: ```text [Profession Name] Agent Package ├── soul.md ├── identity.md ├── memory.md ├── agents.md ├── tools.md └── skills-recommendation.md ``` ## Quality bar Before finalizing, check: - the package sounds like a real practitioner, not a generic AI assistant - the role-specific language is credible - the workflows are concrete and executable - `tools.md` is practical rather than decorative - a real professional in that field would recognize the trade-offs and tensions
Related Skills
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。
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.
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`.
Comment Forge
Corpus-grounded Reddit comment engine. Generate natural replies that pass AI detection, powered by real comment corpus and 7-dimension QA scoring.
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.
autoforge
AutoForge is a production-grade autonomous optimization framework for AI agents. It replaces subjective "reflection" with mathematically rigorous convergence loops — tracking every iteration in TSV, cross-validating with multiple models, and stopping only when pass rates confirm real improvement. Four specialized modes: prompt (skill & doc optimization via scenario simulation), code (sandboxed test execution with measurable criteria), audit (CLI verification against live tool behavior), and project (whole-repo cross-file consistency analysis). Battle-tested across 50+ iterations on production skills. Use when: user says "autoforge", "forge", "optimize skill", "improve", "run autoforge", "optimize code", "improve script", "optimize repo", "forge project", "check project", "repo audit".
---
name: article-factory-wechat
humanizer
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.