sample-oh-my-aidlcops
Health Uyari
- License — License: MIT-0
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 5 GitHub stars
Code Basarisiz
- eval() — Dynamic code execution via eval() in docs/src/components/HomeLanding/index.tsx
Permissions Gecti
- Permissions — No dangerous permissions requested
This project is a plugin marketplace and extension for AI coding assistants like Claude Code and Kiro. It automates the AWS AI-Driven Development Lifecycle (AIDLC) by using agent-based operations to handle everything from project inception and code construction to autonomous cloud deployments and incident response.
Security Assessment
Because this tool is designed to autonomously deploy cloud infrastructure, manage Kubernetes (EKS) clusters, and handle incident responses, it inherently requires access to highly sensitive AWS environments and executes infrastructure-as-code commands. While no hardcoded secrets or explicitly dangerous application permissions were found, the automated nature of its operations poses a significant risk if misconfigured. The rule-based scanner did flag a dynamic code execution vulnerability (`eval()`) in the frontend documentation component, but this is generally isolated to the local web UI and does not impact the core backend infrastructure plugins. Overall risk: Medium.
Quality Assessment
The repository is actively maintained, with its most recent code push happening just today. It is officially backed by AWS (as indicated by the `aws-samples` organization) and is properly licensed under the permissive MIT-0 license, which is excellent for enterprise adoption. However, community visibility and trust are currently very low. The project only has 5 GitHub stars, meaning it has not yet been widely battle-tested or thoroughly reviewed by the broader open-source community.
Verdict
Use with caution: the tool is actively maintained and officially supported by AWS, but its extreme automation capabilities over sensitive cloud environments and lack of widespread community validation require strict human oversight before implementing.
AIDLC × AgenticOps — plugin marketplace that extends Claude Code and Kiro with agentic operations for the AWS AI-Driven Development Lifecycle (Inception → Construction → Operations).
sample-oh-my-aidlcops
AIDLC × AgenticOps — a plugin marketplace that automates the full AI-Driven
Development Lifecycle with agent-based operations on AWS.
한국어 README · Documentation · Plugins · Steering
What is OMA?
oh-my-aidlcops (OMA) is the sibling project of
oh-my-claudecode (OMC).
Where OMC orchestrates generic Claude Code workflows, OMA specializes in the
AIDLC loop: Inception → Construction → Operations.
The thesis: AIDLC is complete only when operations are agent-automated. OMA
fuses the AWS-official AIDLC workflows
with an AgenticOps layer (self-improving feedback loops, autonomous deploys,
continuous evaluation, incident response, cost governance) so the lifecycle
closes itself without human execution at every step.
Who is this for?
- Platform engineers building agentic AI on AWS EKS.
- Teams running LLM/agent workloads who want AIDLC to cover operations, not
just design and construction. - Teams modernizing legacy workloads onto AWS using a repeatable 6R workflow.
- Claude Code or Kiro users who want a drop-in marketplace rather than
hand-rolling skills.
Plugins
| Plugin | What it does | Example skills |
|---|---|---|
agentic-platform |
Build & run the Agentic AI Platform on EKS | agentic-eks-bootstrap, vllm-serving-setup, inference-gateway-routing, langfuse-observability, gpu-resource-management, ai-gateway-guardrails |
agenticops |
Operate it with agents | self-improving-loop, autopilot-deploy, incident-response, continuous-eval, cost-governance, audit-trail |
aidlc-inception |
AIDLC Phase 1 extensions | structured-intake, requirements-analysis, user-stories, workflow-planning |
aidlc-construction |
AIDLC Phase 2 extensions | component-design, code-generation, test-strategy, risk-discovery, quality-gates |
modernization |
Legacy workload modernization to AWS (6R strategy) | workload-assessment, modernization-strategy, to-be-architecture, containerization, cutover-planning |
Tier-0 workflows
OMA inherits the Tier-0 pattern from OMC — high-leverage workflows you invoke
once and let run, with human approval only at checkpoints.
| Command | Purpose |
|---|---|
/oma:autopilot |
Full AIDLC loop autopilot (Inception → Construction → Operations) |
/oma:aidlc-loop |
Single-feature AIDLC one-pass |
/oma:agenticops |
Operations mode (continuous-eval + incident-response + cost-governance) |
/oma:self-improving |
Feedback loop — Langfuse traces to skill/prompt improvement PR |
/oma:platform-bootstrap |
5-checkpoint Agentic AI Platform build on EKS |
/oma:modernize |
Legacy workload modernization (6R decision → cutover) |
/oma:review |
AIDLC artifact review (ADR, spec, design, PR) |
/oma:cancel |
Terminate active Tier-0 mode |
Install
⚡ One-liner (Tech Preview — recommended)
install.sh downloads the pinned release tarball, extracts to ~/.oma, and
symlinks ~/.local/bin/oma. oma setup then writes a project profile,
seeds the ontology, installs the plugins, and runs oma doctor to confirm
the environment.
curl -fsSL https://raw.githubusercontent.com/aws-samples/sample-oh-my-aidlcops/v0.2.0-preview.1/install.sh | bash
cd my-project
oma setup
oma doctor
See the Easy Button docs
for what oma setup writes, how the 12 doctor probes work, and how the
ontology + harness DSL get enforced at runtime.
Tech Preview notice —
v0.2.0-preview.1stabilizesprofile.yamlv1
and the 6 ontology schemas. Everything else (CLI UX, DSL fields, doctor
report shape) may evolve before GA. See Support Policy.
Claude Code (native marketplace)
claude
> /plugin marketplace add https://github.com/aws-samples/sample-oh-my-aidlcops
> /plugin install agentic-platform agenticops aidlc-inception aidlc-construction modernization
Claude Code (manual)
git clone https://github.com/aws-samples/sample-oh-my-aidlcops
bash sample-oh-my-aidlcops/scripts/install/claude.sh
Kiro
git clone https://github.com/aws-samples/sample-oh-my-aidlcops
bash sample-oh-my-aidlcops/scripts/install/kiro.sh
Initialize .omao/ in your project
cd <your-project>
bash <path-to-oma>/scripts/init-omao.sh
AIDLC extensions (opt-in)
bash scripts/install/aidlc-extensions.sh
# Clones awslabs/aidlc-workflows into ~/.aidlc and symlinks OMA's opt-in extensions.
Liked it? Give the repo a Star
If OMA was useful, a ⭐ on the GitHub repository
helps us prioritize maintenance and keeps release notifications flowing
to you. It is entirely optional — nothing in the CLI changes based on
your star status.
Architecture
User request
│
▼
Tier-0 trigger ─── matches keyword? ──▶ /oma:<workflow>
│
▼
Plugin dispatch
│
├─▶ agentic-platform (build)
├─▶ agenticops (operate)
├─▶ aidlc-inception (Phase 1)
├─▶ aidlc-construction (Phase 2)
└─▶ modernization (legacy → AWS)
│
▼
Skills execute, calling AWS Hosted MCP
│
├─▶ eks, cloudwatch, prometheus, aws-iac, cost-explorer, ...
│
▼
Checkpoint — human approves
│
▼
Operations phase continues autonomously
│
└─▶ self-improving-loop feeds corrections back to Construction
Foundation: ontology + harness DSL
OMA plugins rest on two shared layers:
- Ontology (
ontology/,schemas/ontology/) — six JSON Schemas that
define the vocabulary every plugin and skill agrees on:Agent,Skill,Deployment,Incident,Budget,Risk. A handoff between Construction
and Operations is no longer a prose description; it is a validatedDeploymentdocument. See ontology/README.md and
ontology/glossary.md. - Harness DSL (
schemas/harness/dsl.schema.json,tools/oma_compile/) —
one<plugin>.oma.yamlper plugin is the single source of agents, MCP
servers, hooks, and triggers.python -m tools.oma_compiletranslates it
to the native.mcp.jsonandkiro-agents/*.agent.jsonfiles that Claude
Code and Kiro already consume, so marketplace installs stay unchanged.
<plugin>.oma.yaml ──(oma-compile)──▶ .mcp.json
▶ kiro-agents/<agent>.agent.json
▶ .omao/triggers.json (merged across plugins)
CI (.github/workflows/oma-foundation.yml) validates every schema fixture and
runs oma-compile --check to reject drift between DSL sources and committed
native files.
Security posture
This repository ships with conservative defaults. A few things are worth
calling out before you use it in production:
- MCP servers are pinned to exact PyPI versions in every
.mcp.jsonandkiro-agents/*.agent.json.@latestis not used anywhere — a compromised
upstream release cannot silently land alongside AWS credentials. - EKS MCP is read-only by default. The bundled Kiro agent profile does
not pass--allow-writeor--allow-sensitive-data-accesstoawslabs.eks-mcp-server. Add them explicitly when you need to provision
or mutate EKS resources, and audit that change. - IAM is least-privilege. The
langfuse-observabilityskill uses a
customer-managed policy scoped to the Langfuse bucket ARN; AWS managedAmazonS3FullAccess(s3:*account-wide) is explicitly rejected with a
"Bad Example" block in the skill. budget.yamlexpressions are sandboxed. Thecost-governanceskill
evaluatesrule["when"]viasimpleeval
(AST walker, zero builtins, zero callables). A documented Bad Example shows
why Pythoneval()on a user-editable file is an RCE vector.- Session state stays local.
.omao/state/,.omao/plans/,.omao/logs/,.omao/notepad.md, and.omao/project-memory.jsonare gitignored —audit-trailcaptures prompts verbatim (PII, approver identity, SOC2
retention content) and must never leave the machine. - Hooks require a real JSON encoder.
hooks/session-start.shusesjq
(withpython3/pythonas ordered fallbacks) and exits non-zero rather
than emitting shell-interpolated JSON, preventing state-file injection into
the session context.
Reused assets
OMA stands on top of existing AWS and community work rather than reinventing.
| Source | License | How OMA uses it |
|---|---|---|
| awslabs/agent-plugins | Apache-2.0 | Adopts plugin, skill-frontmatter, mcp, marketplace JSON schemas. |
| awslabs/aidlc-workflows | MIT-0 | Consumed as AIDLC core; OMA contributes only *.opt-in.md extensions. |
| awslabs/mcp | Apache-2.0 | 11 hosted MCP servers referenced via uvx stdio. |
| aws-samples/sample-apex-skills | MIT-0 | Workflow 5-checkpoint template pattern. |
| aws-samples/sample-ai-driven-modernization-with-kiro | MIT-0 | Risk-discovery, audit-trail, quality-gates, 6R strategy methodology. |
| Atom-oh/oh-my-cloud-skills | MIT | Eval script patterns, Kiro conversion reference. |
| oh-my-claudecode | — | Tier-0 orchestration and .omc/ state inheritance. |
Full attribution in NOTICE.
License
MIT No Attribution (MIT-0). See LICENSE.
Contributing
OMA is in Tech Preview (v0.2.0-preview.1). See CONTRIBUTING.md for the bug
report and pull request process, and CODE_OF_CONDUCT.md
for the Amazon Open Source Code of Conduct. Issues and PRs are especially
welcome for skill quality, MCP coverage gaps, and Kiro compatibility testing.
For security issues, do not open a public GitHub issue — follow the AWS
vulnerability reporting process
instead.
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