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Agentic Skills Best Practices
Best practices, examples, and training materials for building agent skills. Agent skills are folders of instructions, scripts, and resources that AI agents load dynamically to improve performance on specialized tasks.
Write once, run on any compatible agent. Every skill in this repo follows the open Agent Skills specification using only standard fields — no platform-private extensions. The same skill folder works, unmodified, on any platform that implements the spec: Kiro (IDE and CLI), Claude Code, Claude.ai, the Claude API, and other compatible agents. Skills from this repo have been verified end-to-end on both Kiro and Claude Code (see TESTING.md).
This repo is designed for AWS SAs and developers learning to build skills with Kiro as the primary environment, but nothing here locks you in — the instruction-only skills are fully portable, and the few skills that bundle executable scripts/ additionally require a platform that permits code execution and their listed dependencies.
Flagship Skills
Two battle-tested skills, each validated end-to-end against real AWS infrastructure:
🏗️ agentcore-harness-builder — build AWS Bedrock AgentCore Harness agents
Builds production-ready AWS Bedrock AgentCore Harness agents end to end: declarative model + prompt, Memory, built-in Browser/Code Interpreter, Gateway/MCP tools, inline functions, Skills, Observability, Evaluations, Identity, Policy, and more. Battle-tested against the real AWS API — it encodes ~10 introspection-verified API gotchas (apiFormat, optionalValue per-field, allowedTools, opus-4.8 inference rules, …) plus the Live View human-in-the-loop SSO login workaround, so your agent works on the first deploy instead of the tenth.
🦊 gitlab-ci-kiro-pipeline — AI-powered GitLab CI/CD with Kiro CLI headless + MCP
Builds GitLab CI/CD pipelines (.gitlab-ci.yml) that run Kiro CLI in headless mode as an AI reviewer on every merge request: AI code review, config-drift detection, duplication-sync merge gating via machine-readable verdict lines, change-impact analysis — 12 job recipes with tested prompts and a complete pipeline template. Includes MCP server integration in CI (SonarQube SAST, AWS Knowledge, any customer MCP server): --require-mcp-startup fail-fast, @server tool trusting, and a no-infrastructure smoke test validated live in real MR pipelines. Complements the generic cicd-pipeline skill.
Quickstart
New here? Follow the Kiro Skills Quickstart to go from zero to a working skill in 5 minutes.
To install skills from this repo into Kiro in one step:
./install.sh hello-world api-design git-workflow # or ./install.sh --all
What's Inside
- Example Skills: Production-quality examples in
skills/skills/(creative, technical, enterprise) - Hello World: Minimal working skill to verify your setup in
skills/skills/hello-world/ - Skills Workshop: 6-hour hands-on training in
skills-workshop/ - Skill Template: Starting point for new skills in
skills/template/ - Software Engineering Skills: 8 practical workflow skills covering code review, Git workflow, API design, Docker Compose generation, database schema design, CI/CD pipelines, Terraform modules, and Python project setup
- Secure SDLC Skills: 5 Scrum + DevSecOps role skills (threat modeling, security/user story writing, sprint planning with security debt, sprint security review)
- FSI Compliance: compliance checker mapping changes to PCI-DSS v4.0 and MAS TRM controls, with domain-organized reference files
- Cloud Architecture: AWS Well-Architected review skill with per-pillar reference files (security, reliability, cost, performance, operations, sustainability)
- AI Adoption Skills: code-standards-adopter (make AI-written code match your team's style) and legacy-code-testing (characterization tests before refactoring)
- AWS AI Agent Infrastructure: agentcore-harness-builder — see Flagship Skills above
- Agentic CI/CD: gitlab-ci-kiro-pipeline — GitLab pipelines with Kiro CLI headless AI review jobs and MCP server integration; see Flagship Skills above
Looking for the document skills (docx, pdf, pptx, xlsx)? Those are Anthropic's source-available (not open source) production skills. They were removed from this repo to keep all content under open-source licenses — find them in the official anthropics/skills repository.
Repository Structure
.
├── QUICKSTART.md # 5-minute quickstart guide
├── skills/ # Skills collection (from Anthropic)
│ ├── skills/ # Individual skill folders
│ │ ├── hello-world/ # Minimal example (start here)
│ │ ├── skill-creator/ # Build skills with AI assistance
│ │ ├── frontend-design/ # Example: creative skill
│ │ ├── mcp-builder/ # Example: MCP integration
│ │ ├── api-design/ # Example: engineering workflow skill
│ │ └── ...
│ ├── template/ # Blank skill template
│ └── README.md # Skills collection docs
├── skills-workshop/ # Workshop training materials
│ ├── 01-fundamentals/ # Progressive disclosure, YAML, structure
│ ├── 02-planning-design/ # Use cases, descriptions, triggers
│ ├── 03-testing-iteration/ # Testing strategies
│ ├── 04-distribution-sharing/
│ ├── 05-patterns-troubleshooting/
│ ├── 06-resources-references/
│ └── hands-on-labs/ # 3 hands-on labs (beginner to advanced)
Learning Path
| Step | What | Time |
|---|---|---|
| 1 | Quickstart — copy hello-world, see it trigger | 5 min |
| 2 | Workshop Ch.1 — understand progressive disclosure | 60 min |
| 3 | Lab 1 — build a real skill | 30 min |
| 4 | Browse skills/skills/ — study production patterns |
self-paced |
| 5 | Full Workshop — complete training | 6 hours |
Platform Compatibility
Skills in this repo are portable by construction: they use only the standard fields of the Agent Skills specification (name, description, license, metadata) and no platform-private extensions. Any agent that implements the spec can load them. Platforms verified or documented:
| Platform | Install Location | Docs |
|---|---|---|
| Kiro IDE | ~/.kiro/skills/ (global) or .kiro/skills/ (workspace) |
kiro.dev/docs/skills |
| Kiro CLI | ~/.kiro/skills/ |
kiro.dev/docs/skills |
| Claude Code | ~/.claude/skills/ or via plugin marketplace |
skills/README.md — verified end-to-end, see TESTING.md |
| Claude.ai | Upload as custom skill | Claude Skills Guide |
| Claude API | Via Skills API | Skills API Quickstart |
| Other spec-compatible agents | Per platform | agentskills.io |
Portability notes:
- Instruction-only skills (the Secure SDLC, FSI Compliance, Cloud Architecture, and most engineering skills) are fully portable — they are plain markdown and need nothing from the host beyond spec support.
- Skills bundling executable
scripts/(e.g. test generators, webapp-testing) additionally require a platform that permits code execution and the dependencies each skill declares. - Activation behavior can differ slightly per platform (each agent decides when a description matches); the trigger phrasing in our skill descriptions is tested on Claude Code and follows Kiro's guidance.
Kiro Features
Steering Files
Kiro supports steering files in the .kiro/steering/ directory at your project root. These are markdown files that define project-wide conventions, coding standards, and behavioral rules that Kiro follows whenever it works in your repository.
This repo uses .kiro/steering/conventions.md to enforce consistent formatting, naming, and structure across all contributions.
Project-Level Skills
Skills can be installed at two levels:
| Scope | Location | Use Case |
|---|---|---|
| Project-level | .kiro/skills/ (checked into repo) |
Shared with all contributors; project-specific workflows |
| Global | ~/.kiro/skills/ (user home) |
Personal productivity skills; cross-project utilities |
Project-level skills are version-controlled with your codebase and automatically available to everyone who clones the repo.
Kiro Web
Kiro Web provides browser-based access with two interaction modes:
- Vibe mode - Conversational iteration where you and Kiro go back and forth refining outputs
- Autonomous mode - Kiro works independently on tasks, reporting back when complete
Both modes support skills for enhanced, domain-specific assistance.
Contributing
See CONTRIBUTING.md for guidelines on adding new skills, code standards, and the pull request process.
Continuous Integration
GitHub Actions validates all skills on every push and pull request. The workflow checks SKILL.md frontmatter, required fields, and naming conventions. See .github/workflows/validate-skills.yml for details.
Testing
Skills are tested in four layers — static spec validation, blind trigger routing, independently graded task execution, and real-environment verification on Claude Code. See TESTING.md for the methodology and recorded results.
Reference Documentation
- Agent Skills Specification
- Kiro Skills Documentation
- Claude Skills Overview
- Claude Skills Best Practices
- Anthropic Skills Repository
Repository Guidelines
- No PDF, PPTX, DOCX, or other binary document files (gitignored)
- No PII or customer data
- No hardcoded credentials or secrets
- All content must be under an open-source license (MIT or Apache 2.0; see Licensing below)
Licensing
This repository contains content under two open-source licenses:
| Content | License |
|---|---|
| Repository docs, workshop materials, engineering skills, tooling | MIT |
| Example skills imported from anthropics/skills (e.g. skill-creator, mcp-builder, canvas-design) | Apache 2.0 — see each skill's LICENSE.txt |
Anthropic's source-available document skills (docx, pdf, pptx, xlsx) are not included here; use the official anthropics/skills repository for those.
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