agentfolio

# AgentFolio ## Selective Reading Rule Start with: - `references/senior-master-standard.md` - `references/usage-routing.md` - `references/quality-checklist.md` Then load only the inherited docs, scripts, assets, or examples that match the user's actual task. **Role**: Autonomous Agent Discovery Guide Use this skill when you want to **discover, compare, and research autonomous AI agents** across ecosystems. AgentFolio is a curated directory at https://agentfolio.io that tracks agent frameworks, products, and tools. This skill helps you: - Find existing agents before building your own from scratch. - Map the landscape of agent frameworks and hosted products. - Collect concrete examples and benchmarks for agent capabilities. ## Capabilities - Discover autonomous AI agents, frameworks, and tools by use case. - Compare agents by capabilities, target users, and integration surfaces. - Identify gaps in the market or inspiration for new skills/workflows. - Gather example agent behavior and UX patterns for your own designs. - Track emerging trends in agent architectures and deployments. ## How to Use AgentFolio 1. **Open the directory** - Visit `https://agentfolio.io` in your browser. - Optionally filter by category (e.g., Dev Tools, Ops, Marketing, Productivity). 2. **Search by intent** - Start from the problem you want to solve: - “customer support agents” - “autonomous coding agents” - “research / analysis agents” - Use keywords in the AgentFolio search bar that match your domain or workflow. 3. **Evaluate candidates** - For each interesting agent, capture: - **Core promise** (what outcome it automates). - **Input / output shape** (APIs, UI, data sources). - **Autonomy model** (one-shot, multi-step, tool-using, human-in-the-loop). - **Deployment model** (SaaS, self-hosted, browser, IDE, etc.). 4. **Synthesize insights** - Use findings to: - Decide whether to integrate an existing agent vs. build your own. - Borrow successful UX and safety patterns. - Position your own agent skills and workflows relative to the ecosystem. ## Example Workflows ### 1) Landscape scan before building a new agent - Define the problem: “autonomous test failure triage for CI pipelines”. - Use AgentFolio to search for: - “testing agent”, “CI agent”, “DevOps assistant”, “incident triage”. - For each relevant agent: - Note supported platforms (GitHub, GitLab, Jenkins, etc.). - Capture how they explain autonomy and safety boundaries. - Record pricing/licensing constraints if you plan to adopt instead of build. ### 2) Competitive and inspiration research for a new skill - If you plan to add a new skill (e.g., observability agent, security agent): - Use AgentFolio to find similar agents and features. - Extract 3–5 concrete patterns you want to emulate or avoid. - Translate those patterns into clear requirements for your own skill. ### 3) Vendor shortlisting - When choosing between multiple agent vendors: - Use AgentFolio entries as a neutral directory. - Build a comparison table (columns: capabilities, integrations, pricing, trust & security). - Use that table to drive a more formal evaluation or proof-of-concept. ## Example Prompts Use these prompts when working with this skill in an AI coding agent: - “Use AgentFolio to find 3 autonomous AI agents focused on code review. For each, summarize the core value prop, supported languages, and how they integrate into developer workflows.” - “Scan AgentFolio for agents that help with customer support triage. List the top options, their target customer size (SMB vs. enterprise), and any notable UX patterns.” - “Before we build our own research assistant, use AgentFolio to map existing research / analysis agents and highlight gaps we could fill.” ## When to Use This skill is applicable when you need to **discover or compare autonomous AI agents** instead of building in a vacuum: - At the start of a new agent or workflow project. - When evaluating vendors or tools to integrate. - When you want inspiration or best practices from existing agent products. ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.