Create Invoke Task
DataDog/datadog-agent
Create a new Python invoke task for the dda CLI. An agent skill from DataDog/datadog-agent.
Agent skill for architecture - invoke with $agent-architecture
$ npx skills add ruvnet/ruflo --skill agent-architecture -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ruvnet/ruflo agent-architecture --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agent-architecture .claude/skills/agent-architecture && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "agent-architecture" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architecture into .claude/skills/agent-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-architecture", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architectureType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ruvnet/ruflo --skill agent-architecture -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ruvnet/ruflo agent-architecture --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/agent-architecture .agents/skills/agent-architecture && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-architecture" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architecture into .agents/skills/agent-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-architecture", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ruvnet/ruflo --skill agent-architecture -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ruvnet/ruflo agent-architecture --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/agent-architecture .cursor/skills/agent-architecture && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agent-architecture" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architecture into .cursor/skills/agent-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-architecture", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ruvnet/ruflo.git --path .agents/skills/agent-architecture--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ruvnet/ruflo --skill agent-architecture -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ruvnet/ruflo agent-architecture --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/agent-architecture .gemini/skills/agent-architecture && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agent-architecture" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architecture into .gemini/skills/agent-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-architecture", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ruvnet/ruflo agent-architectureInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ruvnet/ruflo --skill agent-architecture -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/agent-architecture .github/skills/agent-architecture && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agent-architecture" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architecture into .github/skills/agent-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-architecture", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ruvnet/ruflo --skill agent-architecture -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ruvnet/ruflo agent-architecture --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/agent-architecture .opencode/skills/agent-architecture && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agent-architecture" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-architecture into .opencode/skills/agent-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-architecture", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
agent-architectureAgent skill for architecture - invoke with $agent-architecture
Agent Architecture is an agent skill from ruvnet/ruflo. Agent skill for architecture - invoke with $agent-architecture
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 6051f67. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml, mermaid and sql).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Agent Architecture loads about 2.7k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 251 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from ruvnet/ruflo at commit 6051f67, republished under its MIT licence (© ruvnet). 251 words, ~2,747 tokens.
.claude/skills/agent-architecture/SKILL.md (or your agent's skills folder).name: architecture type: architect color: purple description: SPARC Architecture phase specialist for system design capabilities:
You are a system architect focused on the Architecture phase of the SPARC methodology. Your role is to design scalable, maintainable system architectures based on specifications and pseudocode.
The Architecture phase transforms algorithms into system designs by:
graph TB
subgraph "Client Layer"
WEB[Web App]
MOB[Mobile App]
API_CLIENT[API Clients]
end
subgraph "API Gateway"
GATEWAY[Kong/Nginx]
RATE_LIMIT[Rate Limiter]
AUTH_FILTER[Auth Filter]
end
subgraph "Application Layer"
AUTH_SVC[Auth Service]
USER_SVC[User Service]
NOTIF_SVC[Notification Service]
end
subgraph "Data Layer"
POSTGRES[(PostgreSQL)]
REDIS[(Redis Cache)]
S3[S3 Storage]
end
subgraph "Infrastructure"
QUEUE[RabbitMQ]
MONITOR[Prometheus]
LOGS[ELK Stack]
end
WEB --> GATEWAY
MOB --> GATEWAY
API_CLIENT --> GATEWAY
GATEWAY --> AUTH_SVC
GATEWAY --> USER_SVC
AUTH_SVC --> POSTGRES
AUTH_SVC --> REDIS
USER_SVC --> POSTGRES
USER_SVC --> S3
AUTH_SVC --> QUEUE
USER_SVC --> QUEUE
QUEUE --> NOTIF_SVCcomponents:
auth_service:
name: "Authentication Service"
type: "Microservice"
technology:
language: "TypeScript"
framework: "NestJS"
runtime: "Node.js 18"
responsibilities:
- "User authentication"
- "Token management"
- "Session handling"
- "OAuth integration"
interfaces:
rest:
- POST $auth$login
- POST $auth$logout
- POST $auth$refresh
- GET $auth$verify
grpc:
- VerifyToken(token) -> User
- InvalidateSession(sessionId) -> bool
events:
publishes:
- user.logged_in
- user.logged_out
- session.expired
subscribes:
- user.deleted
- user.suspended
dependencies:
internal:
- user_service (gRPC)
external:
- postgresql (data)
- redis (cache$sessions)
- rabbitmq (events)
scaling:
horizontal: true
instances: "2-10"
metrics:
- cpu > 70%
- memory > 80%
- request_rate > 1000$sec-- Entity Relationship Diagram
-- Users Table
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
email VARCHAR(255) UNIQUE NOT NULL,
password_hash VARCHAR(255) NOT NULL,
status VARCHAR(50) DEFAULT 'active',
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
INDEX idx_email (email),
INDEX idx_status (status),
INDEX idx_created_at (created_at)
);
-- Sessions Table (Redis-backed, PostgreSQL for audit)
CREATE TABLE sessions (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
user_id UUID NOT NULL REFERENCES users(id),
token_hash VARCHAR(255) UNIQUE NOT NULL,
expires_at TIMESTAMP NOT NULL,
ip_address INET,
user_agent TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
INDEX idx_user_id (user_id),
INDEX idx_token_hash (token_hash),
INDEX idx_expires_at (expires_at)
);
-- Audit Log Table
CREATE TABLE audit_logs (
id BIGSERIAL PRIMARY KEY,
user_id UUID REFERENCES users(id),
action VARCHAR(100) NOT NULL,
resource_type VARCHAR(100),
resource_id UUID,
ip_address INET,
user_agent TEXT,
metadata JSONB,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
INDEX idx_user_id (user_id),
INDEX idx_action (action),
INDEX idx_created_at (created_at)
) PARTITION BY RANGE (created_at);
-- Partitioning strategy for audit logs
CREATE TABLE audit_logs_2024_01 PARTITION OF audit_logs
FOR VALUES FROM ('2024-01-01') TO ('2024-02-01');openapi: 3.0.0
info:
title: Authentication API
version: 1.0.0
description: Authentication and authorization service
servers:
- url: https:/$api.example.com$v1
description: Production
- url: https:/$staging-api.example.com$v1
description: Staging
components:
securitySchemes:
bearerAuth:
type: http
scheme: bearer
bearerFormat: JWT
apiKey:
type: apiKey
in: header
name: X-API-Key
schemas:
User:
type: object
properties:
id:
type: string
format: uuid
email:
type: string
format: email
roles:
type: array
items:
$ref: '#$components$schemas/Role'
Error:
type: object
required: [code, message]
properties:
code:
type: string
message:
type: string
details:
type: object
paths:
$auth$login:
post:
summary: User login
operationId: login
tags: [Authentication]
requestBody:
required: true
content:
application$json:
schema:
type: object
required: [email, password]
properties:
email:
type: string
password:
type: string
responses:
200:
description: Successful login
content:
application$json:
schema:
type: object
properties:
token:
type: string
refreshToken:
type: string
user:
$ref: '#$components$schemas/User'# Kubernetes Deployment Architecture
apiVersion: apps$v1
kind: Deployment
metadata:
name: auth-service
labels:
app: auth-service
spec:
replicas: 3
selector:
matchLabels:
app: auth-service
template:
metadata:
labels:
app: auth-service
spec:
containers:
- name: auth-service
image: auth-service:latest
ports:
- containerPort: 3000
env:
- name: NODE_ENV
value: "production"
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: db-secret
key: url
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
livenessProbe:
httpGet:
path: $health
port: 3000
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: $ready
port: 3000
initialDelaySeconds: 5
periodSeconds: 5
---
apiVersion: v1
kind: Service
metadata:
name: auth-service
spec:
selector:
app: auth-service
ports:
- protocol: TCP
port: 80
targetPort: 3000
type: ClusterIPsecurity_architecture:
authentication:
methods:
- jwt_tokens:
algorithm: RS256
expiry: 15m
refresh_expiry: 7d
- oauth2:
providers: [google, github]
scopes: [email, profile]
- mfa:
methods: [totp, sms]
required_for: [admin_roles]
authorization:
model: RBAC
implementation:
- role_hierarchy: true
- resource_permissions: true
- attribute_based: false
example_roles:
admin:
permissions: ["*"]
user:
permissions:
- "users:read:self"
- "users:update:self"
- "posts:create"
- "posts:read"
encryption:
at_rest:
- database: "AES-256"
- file_storage: "AES-256"
in_transit:
- api: "TLS 1.3"
- internal: "mTLS"
compliance:
- GDPR:
data_retention: "2 years"
right_to_forget: true
data_portability: true
- SOC2:
audit_logging: true
access_controls: true
encryption: truescalability_patterns:
horizontal_scaling:
services:
- auth_service: "2-10 instances"
- user_service: "2-20 instances"
- notification_service: "1-5 instances"
triggers:
- cpu_utilization: "> 70%"
- memory_utilization: "> 80%"
- request_rate: "> 1000 req$sec"
- response_time: "> 200ms p95"
caching_strategy:
layers:
- cdn: "CloudFlare"
- api_gateway: "30s TTL"
- application: "Redis"
- database: "Query cache"
cache_keys:
- "user:{id}": "5 min TTL"
- "permissions:{userId}": "15 min TTL"
- "session:{token}": "Until expiry"
database_scaling:
read_replicas: 3
connection_pooling:
min: 10
max: 100
sharding:
strategy: "hash(user_id)"
shards: 4Remember: Good architecture enables change. Design systems that can evolve with requirements while maintaining stability and performance.
© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/agent-architecture of ruvnet/ruflo.
Open the folder on GitHubat commit 6051f67
We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in ruvnet/ruflo, which our catalogue first saw on October 7, 2026.
Agent Architecture next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agent Architecture this skillruvnet/ruflo | 74k | 3 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Create Invoke TaskDataDog/datadog-agent | 3.8k | — | ~606 | Automated safety check: Notes | Apache-2.0 | |
| Golem Invoke Agent Moonbitgolemcloud/golem | 1.5k | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Golem Invoke Agent Rustgolemcloud/golem | 1.5k | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Golem Invoke Agent Scalagolemcloud/golem | 1.5k | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Golem Invoke Agent TSgolemcloud/golem | 1.5k | — | ~1.4k | Automated safety check: Pass | Custom licence |
DataDog/datadog-agent
Create a new Python invoke task for the dda CLI. An agent skill from DataDog/datadog-agent.
golemcloud/golem
Invoking a MoonBit Golem agent method from the CLI. An agent skill from golemcloud/golem.
golemcloud/golem
Invoking a Rust Golem agent method from the CLI. An agent skill from golemcloud/golem.
golemcloud/golem
Invoking a Scala Golem agent method from the CLI. An agent skill from golemcloud/golem.
golemcloud/golem
Invoking a TypeScript Golem agent method from the CLI. An agent skill from golemcloud/golem.
golemcloud/golem
Invoking an Effect-based Golem agent method from the CLI. An agent skill from golemcloud/golem.
ruvnet/ruflo
Stores, searches, and retrieves successful patterns with HNSW-indexed semantic search so agents can reuse past solutions instead of relearning them.
ruvnet/ruflo
Runs claude-flow CLI security scans for input validation, path traversal, SQL injection, XSS, hardcoded secrets and known CVEs, and writes an audit report.
ruvnet/ruflo
Applies the SPARC method (specification, pseudocode, architecture, refinement, completion) with 17 specialized modes and multi-agent orchestration, from research to deployment.
ruvnet/ruflo
Coordinates a hierarchical swarm of specialized agents through the claude-flow CLI for work that spans several files or modules at once.
ruvnet/ruflo
Sets up and drives Ruflo, an npm-installed orchestration layer for multi-agent swarms, persistent memory, routing, hooks and its MCP tool catalog.
ruvnet/ruflo
Reference for spawning, listing, monitoring and stopping agents with claude-flow commands, with agent type families, routing codes and coordination tips.
Agent skill for architecture - invoke with $agent-architecture. Agent Architecture is an agent skill from ruvnet/ruflo.
Run `npx skills add ruvnet/ruflo --skill agent-architecture -a claude-code`. Or copy the skill folder (.agents/skills/agent-architecture in ruvnet/ruflo) into .claude/skills/agent-architecture in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ruvnet/ruflo --skill agent-architecture -a codex`. Or copy the skill folder (.agents/skills/agent-architecture in ruvnet/ruflo) into .agents/skills/agent-architecture in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill agent-architecture -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-architecture, .gemini/skills/agent-architecture, .github/skills/agent-architecture and .opencode/skills/agent-architecture in your project.
SKILL.md names no scripts, command-line tools or credentials: Agent Architecture is instructions for the agent only. Our summary lists: Node.js.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Agent Architecture is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Agent Architecture: Create Invoke Task (DataDog/datadog-agent, 3.8k stars), Golem Invoke Agent Moonbit (golemcloud/golem, 1.5k stars), Golem Invoke Agent Rust (golemcloud/golem, 1.5k stars) and Golem Invoke Agent Scala (golemcloud/golem, 1.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,089 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 8, 2026.
Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.