AgentFolio workflow skill. Use this skill when the user needs Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
Instrucciones de origen · Vista previa de solo lectura
name
agentfolio
description
AgentFolio workflow skill. Use this skill when the user needs Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/agentfolio from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
AgentFolio 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.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Capabilities, How to Use AgentFolio, Limitations.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
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.
Use when the request clearly matches the imported source intent: Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Use when provenance needs to stay visible in the answer, PR, or review packet.
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Define the problem: “autonomous test failure triage for CI pipelines”.
Use that table to drive a more formal evaluation or proof-of-concept.
Imported: 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.
Examples
Example 1: Ask for the upstream workflow directly
Use @agentfolio to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @agentfolio against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @agentfolio for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @agentfolio using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Imported Usage Notes
Imported: 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.”
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
Treat generated examples as scaffolding; adapt them to the concrete task before execution.
Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/agentfolio, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a
Imported Reference Notes
Imported: How to Use AgentFolio
Open the directory
Visit https://agentfolio.io in your browser.
Optionally filter by category (e.g., Dev Tools, Ops, Marketing, Productivity).
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.
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.).
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.
Imported: 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.
