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jabir-srj

Agency Agents Wrapper

by Jabir Iliyas Suraj-Deen · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install agency-agents-wrapper
Description
Activate specialized AI agent personas across 18+ domains with tailored expertise, workflows, communication styles, and technical deliverables.
README (SKILL.md)

Agency Agents

The Agency is a collection of meticulously crafted AI agent personalities, each with:

  • Deep expertise in their domain (not generic templates)
  • Unique voice and communication style
  • Proven workflows and success metrics
  • Technical deliverables with code examples

Quick Start

Browse Available Agents

Agents are organized by domain. List available agents:

ls -la references/agents/

Each .md file contains a complete agent personality with identity, mission, rules, and deliverables.

Major domains:

  • engineering/ — Backend, Frontend, DevOps, Security, ML, etc.
  • product/ — Product Managers, UX Designers, Growth strategists
  • sales/ — Sales specialists, Account Executives, Deal closers
  • marketing/ — Content, Paid Media, Community, Growth
  • design/ — UI/UX, Brand, Product Design
  • strategy/ — Consultants, Analysts, Business strategists
  • support/ — Customer Success, Support specialists
  • testing/ — QA Engineers, Test strategists
  • And more: academic/, game-development/, integrations/, specialized/

Activate an Agent

  1. Find the agent in references/agents/\x3Cdomain>/ (e.g., engineering-frontend-developer.md)
  2. Read the agent file to absorb personality, mission, and workflows
  3. Adopt the persona — use the agent's voice, approach, and technical style for your current task
  4. Follow their rules — each agent has critical guidelines and success metrics

Example: Frontend Developer

Read references/agents/engineering/engineering-frontend-developer.md, then work with:

  • Their performance-first mindset
  • Accessibility and inclusive design focus
  • Technical deliverables (React components, PWAs, design systems)
  • Communication style (detail-oriented, user-centric, precise)

Agent Structure

Each agent file contains:

---
name: Agent Name
description: Brief description
color: Visual indicator
emoji: 🎭
vibe: One-liner describing their energy
---

# Agent Personality

## 🧠 Identity & Memory
- Role, personality, experience

## 🎯 Core Mission
- Primary responsibilities
- Technical domains
- Key deliverables

## 🚨 Critical Rules
- Non-negotiable guidelines
- Quality standards
- Red lines

## 📋 Technical Deliverables
- Code examples
- Templates
- Proven patterns

## 💬 Communication Style
- Tone and voice
- How they interact
- Success metrics

Workflow: Task-Agent Matching

When facing a complex task:

  1. Identify the domain — What expertise does this need? (engineering, marketing, sales, etc.)
  2. Find the best agent — Browse that domain folder for the closest match
  3. Read their profile — Understand their perspective, priorities, and rules
  4. Adopt their approach — Use their workflows, communication style, and technical standards
  5. Execute — Apply their expertise and deliverables to your task

Example flow:

  • Task: "Build a responsive dashboard"
  • Domain: Engineering (Frontend)
  • Agent: engineering-frontend-developer.md
  • Adopt: Performance-first, accessibility-focused, Core Web Vitals optimization
  • Execute: Build with their rules, code examples, and UX patterns

Tips for Effective Agent Use

🎯 Specificity Matters

  • Don't just activate "Engineer" — pick a specific role like Frontend Developer, Backend Architect, or DevOps Automator
  • The more specific the agent, the more tailored their expertise

📚 Read Actively

  • Each agent file is self-contained and comprehensive
  • Reading takes 2-3 minutes; the detail is worth it
  • You'll pick up their mental models and priorities

🔄 Mix and Match

  • You can combine insights from multiple agents (e.g., Frontend Developer + UX Designer for a UI project)
  • Cross-domain personas often have complementary perspectives

✅ Follow Their Rules

  • Each agent has non-negotiable guidelines ("Critical Rules")
  • These aren't suggestions — they're their professional standards
  • Following them ensures quality output

Available Agent Categories

Domain Focus Example Agents
Engineering 23 roles Frontend Dev, Backend Architect, DevOps, Security, ML, etc.
Product 8 roles Product Manager, UX Designer, Growth, Analytics
Sales 6 roles Sales Rep, Account Exec, Deal Closer, Pipeline builder
Marketing 8 roles Content, Paid Media, Community, Growth, Brand
Design 7 roles UI/UX, Product Design, Brand, Design System
Strategy 5 roles Consultant, Analyst, Business Strategist
Support 4 roles Customer Success, Support, Community
Testing 4 roles QA Engineer, Test Strategist, Automation
Other 12+ roles Academic, Game Dev, Integrations, Specialized

Reference Structure

All agent files are stored in references/agents/\x3Cdomain>/ following the source repository structure. Each file is a standalone personality — load only the ones you need.

To see available agents, explore:

  • references/agents/engineering/ — All engineering specialties
  • references/agents/product/ — Product and UX roles
  • references/agents/sales/ — Sales professionals
  • (and so on for all domains)
Usage Guidance
This package appears coherent for the stated purpose (a local collection of agent/persona files). Before enabling: (1) inspect the one included shell script (references/agents/integrations/mcp-memory/setup.sh) — do not run it unless you trust its contents, (2) confirm the skill's origin since registry metadata lists 'unknown' and there's no homepage, and (3) remember that although the skill itself requests no secrets, personas may ask you for context during use; don't paste sensitive credentials into chats. If you want extra caution, open the repository files yourself and verify there are no embedded external endpoints or secret-collection prompts in the persona MDs before use.
Capability Analysis
Type: OpenClaw Skill Name: agency-agents-wrapper Version: 1.0.0 The skill bundle provides a comprehensive and well-documented framework for adopting specialized AI personas and orchestrating multi-agent workflows. The content primarily consists of markdown-based persona definitions and operational playbooks designed for professional expertise. While a technical vulnerability exists in 'engineering-ai-data-remediation-engineer.md' due to the use of eval() on AI-generated strings, the script includes explicit safety gates and forbidden-term checks (e.g., blocking 'import', 'os', and 'subprocess') to mitigate RCE risks. No evidence of malicious intent, data exfiltration, or unauthorized persistence was found.
Capability Tags
cryptorequires-walletcan-make-purchasescan-sign-transactionsrequires-oauth-token
Capability Assessment
Purpose & Capability
Name/description promise (activate pre-built agent personas) matches the bundle: the repository contains many .md persona files organized by domain and the SKILL.md tells the agent to list/read those files. There are no unrelated environment variables, binaries, or config paths required.
Instruction Scope
SKILL.md only instructs the agent to browse and read local markdown persona files (e.g., ls and open references/agents/...). It does not direct the agent to read system files, access external endpoints, collect or transmit user secrets, or run arbitrary commands beyond listing/reading these repository files.
Install Mechanism
No install spec is present (instruction-only), which is lowest-risk. There is one shell script file present (references/agents/integrations/mcp-memory/setup.sh) but SKILL.md does not instruct running it. Presence of that script is plausible for an integrations subfolder and is not by itself evidence of an installer or remote download.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. Nothing in SKILL.md tries to access undeclared env vars or credentials.
Persistence & Privilege
Flags show always:false and normal model invocation; the skill does not request permanent presence or system-wide configuration changes in its instructions. Nothing in the files indicates modification of other skills or system settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agency-agents-wrapper
  3. After installation, invoke the skill by name or use /agency-agents-wrapper
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial public release of agency-agents-wrapper - Introduces a comprehensive library of pre-built AI agent personas across 18+ professional domains (engineering, marketing, sales, product, design, support, and more). - Each agent profile includes unique voice, deep expertise, proven workflows, rules, communication style, and technical deliverables. - Guides users through browsing, activating, and adopting specialized agent personas for focused, domain-specific tasks. - Provides clear structure for agent files and best practices for effective use, including task-agent matching and combining multiple agents. - Designed for quick onboarding and high-quality, professional outputs by following each agent's critical rules and workflows.
Metadata
Slug agency-agents-wrapper
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Agency Agents Wrapper?

Activate specialized AI agent personas across 18+ domains with tailored expertise, workflows, communication styles, and technical deliverables. It is an AI Agent Skill for Claude Code / OpenClaw, with 110 downloads so far.

How do I install Agency Agents Wrapper?

Run "/install agency-agents-wrapper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agency Agents Wrapper free?

Yes, Agency Agents Wrapper is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agency Agents Wrapper support?

Agency Agents Wrapper is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agency Agents Wrapper?

It is built and maintained by Jabir Iliyas Suraj-Deen (@jabir-srj); the current version is v1.0.0.

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