chore(ci): lint markdown files

.github/workflows/markdownlint.yaml

@@ -0,0 +1,30 @@
+# .github/workflows/markdownlint.yml
+name: Lint
+
+on:
+  push:
+    paths:
+      - '**/*.md'
+      - '.github/workflows/markdownlint.yaml'
+    branches:
+      - main
+  pull_request:
+    paths:
+      - '**/*.md'
+      - '.github/workflows/markdownlint.yaml'
+
+permissions:
+  contents: read
+
+jobs:
+  lint-markdown:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+
+      - name: Install Task
+        uses: arduino/setup-task@8b35f53e4d5a51bf691c94c71f2c7222483206cb
+
+      - name: Lint Markdown Files
+        run: task lint:markdown

.markdownlint-cli2.yaml

@@ -0,0 +1,7 @@
+# Define glob expressions to use (only valid at root)
+globs:
+  - "**/*.md"
+ignores:
+  - "**/.venv/**"
+# Show found files on stdout (only valid at root)
+showFound: true

.markdownlint.yaml

@@ -0,0 +1,21 @@
+# .markdownlint.yaml
+
+# MD001: Heading levels should only increment by one level at a time
+MD001: false
+
+# MD004: Unordered list style - allow different styles in sublists
+MD004:
+  style: sublist
+
+# MD013: Line length
+MD013:
+  line_length: 120
+  code_blocks: false
+  tables: false
+
+# MD025: Multiple top-level headings allowed
+MD025: false
+
+# MD033: Inline HTML
+MD033:
+  allowed_elements: [p, img]

README.md

@@ -2,43 +2,50 @@
 
 ## Prerequisites
 
-+ **[Docker Desktop](https://www.docker.com/products/docker-desktop/) 4.43.0+ or [Docker Engine](https://docs.docker.com/engine/)** installed
-+ **A laptop or workstation with a GPU** (e.g., a MacBook) for running open models locally. If you don't have a GPU, you can alternatively use [**Docker Offload**](https://www.docker.com/products/docker-offload).
-+ If you're using Docker Engine on Linux or Docker Desktop on Windows, ensure that the [Docker Model Runner requirements](https://docs.docker.com/ai/model-runner/) are met (specifically that GPU support is enabled) and the necessary drivers are installed
-+ If you're using Docker Engine on Linux, ensure you have Compose 2.38.1 or later installed
++ **[Docker Desktop] 4.43.0+ or [Docker Engine]** installed.
++ **A laptop or workstation with a GPU** (e.g., a MacBook) for running open models locally. If you
+  don't have a GPU, you can alternatively use **[Docker Offload]**.
++ If you're using [Docker Engine] on Linux or [Docker Desktop] on Windows, ensure that the
+  [Docker Model Runner requirements] are met (specifically that GPU
+  support is enabled) and the necessary drivers are installed.
++ If you're using Docker Engine on Linux, ensure you have [Docker Compose] 2.38.1 or later installed.
 
 ## Demos
 
-Each of these demos is self-contained and can be run either locally or using a cloud context. They are all configured using two steps.
+Each of these demos is self-contained and can be run either locally or using a cloud context. They
+are all configured using two steps.
 
 1. change directory to the root of the demo project
-1. create a `.mcp.env` file from the `mcp.env.example` file (if it exists, otherwise the demo doesn't need any secrets) and supply the required MCP tokens
-1. run `docker compose up --build`
+2. create a `.mcp.env` file from the `mcp.env.example` file (if it exists, otherwise the demo
+   doesn't need any secrets) and supply the required MCP tokens
+3. run `docker compose up --build`
 
 ### Using OpenAI models
 
 The demos support using OpenAI models instead of running models locally with Docker Model Runner. To use OpenAI:
+
 1. Create a `secret.openai-api-key` file with your OpenAI API key:
 
-```
-sk-...
-```
+    ```plaintext
+    sk-...
+    ```
+
 2. Start the project with the OpenAI configuration:
 
-```
-docker compose -f compose.yaml -f compose.openai.yaml up
-```
+    ```sh
+    docker compose -f compose.yaml -f compose.openai.yaml up
+    ```
 
 # Compose for Agents Demos - Classification
 
 | Demo | Agent System | Models | MCPs | project | compose |
 | ---- | ---- | ---- | ---- | ---- | ---- |
-| [A2A](https://github.com/a2a-agents/agent2agent) Multi-Agent Fact Checker | Multi-Agent | OpenAI | duckduckgo | [./a2a](./a2a) | [compose.yaml](./a2a/compose.yaml) | 
+| [A2A](https://github.com/a2a-agents/agent2agent) Multi-Agent Fact Checker | Multi-Agent | OpenAI | duckduckgo | [./a2a](./a2a) | [compose.yaml](./a2a/compose.yaml) |
 | [Agno](https://github.com/agno-agi/agno) agent that summarizes GitHub issues | Multi-Agent | qwen3(local) | github-official | [./agno](./agno) | [compose.yaml](./agno/compose.yaml) |
 | [Vercel AI-SDK](https://github.com/vercel/ai) Chat-UI for mixing MCPs and Model | Single Agent | llama3.2(local), qwen3(local) | wikipedia-mcp, brave, resend(email) | [./vercel](./vercel) | [compose.yaml](https://github.com/slimslenderslacks/scira-mcp-chat/blob/main/compose.yaml) |
 | [CrewAI](https://github.com/crewAIInc/crewAI) Marketing Strategy Agent | Multi-Agent | qwen3(local) | duckduckgo | [./crew-ai](./crew-ai) | [compose.yaml](https://github.com/docker/compose-agents-demo/blob/main/crew-ai/compose.yaml) |
 | [ADK](https://github.com/google/adk-python) Multi-Agent Fact Checker | Multi-Agent | gemma3-qat(local) | duckduckgo | [./adk](./adk) | [compose.yaml](./adk/compose.yaml) |
-| [ADK](https://github.com/google/adk-python) & [Cerebras](https://www.cerebras.ai/) Golang Experts | Multi-Agent | unsloth/qwen3-gguf:4B-UD-Q4_K_XL & ai/qwen2.5:latest (DMR local), llama-4-scout-17b-16e-instruct (Cerebras remote) |  | [./adk-cerebras](./adk-cerebras) | [compose.yml](./adk-cerebras/compose.yml) | 
+| [ADK](https://github.com/google/adk-python) & [Cerebras](https://www.cerebras.ai/) Golang Experts | Multi-Agent | unsloth/qwen3-gguf:4B-UD-Q4_K_XL & ai/qwen2.5:latest (DMR local), llama-4-scout-17b-16e-instruct (Cerebras remote) |  | [./adk-cerebras](./adk-cerebras) | [compose.yml](./adk-cerebras/compose.yml) |
 | [LangGraph](https://github.com/langchain-ai/langgraph) SQL Agent | Single Agent | qwen3(local) | postgres | [./langgraph](./langgraph) | [compose.yaml](./langgraph/compose.yaml) |
 | [Embabel](https://github.com/embabel/embabel-agent) Travel Agent | Multi-Agent | qwen3, Claude3.7, llama3.2, jimclark106/all-minilm:23M-F16 | brave, github-official, wikipedia-mcp, weather, google-maps, airbnb | [./embabel](./embabel) | [compose.yaml](https://github.com/embabel/travel-planner-agent/blob/main/compose.yaml) and [compose.dmr.yaml](https://github.com/embabel/travel-planner-agent/blob/main/compose.dmr.yaml) |
 | [Spring AI](https://spring.io/projects/spring-ai) Brave Search | Single Agent | none | duckduckgo | [./spring-ai](./spring-ai) | [compose.yaml](./spring-ai/compose.yaml) |
@@ -54,3 +61,9 @@ made by Docker in this repository.
 > apply to that specific example, and they must be respected accordingly.
 
 `SPDX-License-Identifier: Apache-2.0 OR MIT`
+
+[Docker Compose]: https://github.com/docker/compose
+[Docker Desktop]: https://www.docker.com/products/docker-desktop/
+[Docker Engine]: https://docs.docker.com/engine/
+[Docker Model Runner requirements]: https://docs.docker.com/ai/model-runner/
+[Docker Offload]: https://www.docker.com/products/docker-offload/

Taskfile.yaml

@@ -0,0 +1,21 @@
+version: '3'
+
+vars:
+  MARKDOWN_CLI2_CMD: docker run --rm -v $(pwd):/workdir davidanson/markdownlint-cli2:v0.18.1
+
+tasks:
+  lint:markdown:
+    desc: Lint Markdown files
+    cmds:
+      - "{{ .MARKDOWN_CLI2_CMD }}"
+    dir: .
+  lint:markdown:fix:
+    desc: Lint and Fix Markdown files
+    cmds:
+      - "{{ .MARKDOWN_CLI2_CMD }} --fix"
+    dir: .
+
+  lint:
+    deps:
+      - lint:markdown
+    desc: Lint all files

a2a/README.md

@@ -10,7 +10,6 @@ internal reasoning alone. The system showcases how agents with distinct roles an
 > [!Tip]
 > ✨ No configuration needed — run it with a single command.
 
-
 <p align="center">
   <img src="demo.gif"
        alt="A2A Multi-Agent Fact Check Demo"
@@ -22,17 +21,20 @@ internal reasoning alone. The system showcases how agents with distinct roles an
 
 ### Requirements
 
-+ **[Docker Desktop](https://www.docker.com/products/docker-desktop/) 4.43.0+ or [Docker Engine](https://docs.docker.com/engine/)** installed
-+ **A laptop or workstation with a GPU** (e.g., a MacBook) for running open models locally. If you don't have a GPU, you can alternatively use [**Docker Offload**](https://www.docker.com/products/docker-offload).
-+ If you're using Docker Engine on Linux or Docker Desktop on Windows, ensure that the [Docker Model Runner requirements](https://docs.docker.com/ai/model-runner/) are met (specifically that GPU support is enabled) and the necessary drivers are installed
-+ If you're using Docker Engine on Linux, ensure you have Compose 2.38.1 or later installed
-+ An [OpenAI API Key](https://platform.openai.com/api-keys) 🔑
++ **[Docker Desktop] 4.43.0+ or [Docker Engine]** installed.
++ **A laptop or workstation with a GPU** (e.g., a MacBook) for running open models locally. If you
+  don't have a GPU, you can alternatively use **[Docker Offload]**.
++ If you're using [Docker Engine] on Linux or [Docker Desktop] on Windows, ensure that the
+  [Docker Model Runner requirements] are met (specifically that GPU
+  support is enabled) and the necessary drivers are installed.
++ If you're using Docker Engine on Linux, ensure you have [Docker Compose] 2.38.1 or later installed.
++ An [OpenAI API Key](https://platform.openai.com/api-keys) 🔑.
 
 ### Run the project
 
 Create a `secret.openai-api-key` file with your OpenAI API key:
 
-```
+```plaintext
 sk-...
 ```
 
@@ -61,18 +63,17 @@ same demo with a larger model that takes advantage of a more powerful GPU on the
 docker compose -f compose.dmr.yaml -f compose.offload.yaml up --build
 ```
 
-
 # ❓ What Can It Do?
 
 This system performs multi-agent fact verification, coordinated by an **Auditor**:
 
-- 🧑‍⚖️ **Auditor**:
-  - Orchestrates the process from input to verdict.
-  - Delegates tasks to Critic and Reviser agents.
-- 🧠 **Critic**:
-	- Uses DuckDuckGo via MCP to gather real-time external evidence.
--	✍️ **Reviser**:
-	- Refines and verifies the Critic’s conclusions using only reasoning.
++ 🧑‍⚖️ **Auditor**:
+  * Orchestrates the process from input to verdict.
+  * Delegates tasks to Critic and Reviser agents.
++ 🧠 **Critic**:
+  * Uses DuckDuckGo via MCP to gather real-time external evidence.
++ ✍️ **Reviser**:
+  * Refines and verifies the Critic’s conclusions using only reasoning.
 
 **🧠 All agents use the Docker Model Runner for LLM-based inference.**
 
@@ -89,7 +90,6 @@ Example question:
 | `src/AgentKit`  | Agent runtime                           |
 | `agents/*.yaml` | Agent definitions                       |
 
-
 # 🔧 Architecture Overview
 
 ```mermaid
@@ -115,10 +115,10 @@ flowchart TD
 
 ```
 
-- The Auditor is a Sequential Agent, it coordinates Critic and Reviser agents to verify user-provided claims.
-- The Critic agent performs live web searches through DuckDuckGo using an MCP-compatible gateway.
-- The Reviser agent refines the Critic’s conclusions using internal reasoning alone.
-- All agents run inference through a Docker-hosted Model Runner, enabling fully containerized LLM reasoning.
++ The Auditor is a Sequential Agent, it coordinates Critic and Reviser agents to verify user-provided claims.
++ The Critic agent performs live web searches through DuckDuckGo using an MCP-compatible gateway.
++ The Reviser agent refines the Critic’s conclusions using internal reasoning alone.
++ All agents run inference through a Docker-hosted Model Runner, enabling fully containerized LLM reasoning.
 
 # 🤝 Agent Roles
 
@@ -128,7 +128,6 @@ flowchart TD
 | **Critic**  | ✅ DuckDuckGo via MCP | Gathers evidence to support or refute the claim                              |
 | **Reviser** | ❌ None               | Refines and finalizes the answer without external input                      |
 
-
 # 🧹 Cleanup
 
 To stop and remove containers and volumes:
@@ -137,15 +136,16 @@ To stop and remove containers and volumes:
 docker compose down -v
 ```
 
-
 # 📎 Credits
-- [A2A]
-- [DuckDuckGo]
-- [Docker Compose]
 
++ [A2A]
++ [DuckDuckGo]
++ [Docker Compose]
 
 [A2A]: https://github.com/a2aproject/a2a-python
 [DuckDuckGo]: https://duckduckgo.com
 [Docker Compose]: https://github.com/docker/compose
 [Docker Desktop]: https://www.docker.com/products/docker-desktop/
-[Docker Model Runner]: https://docs.docker.com/ai/model-runner/
+[Docker Engine]: https://docs.docker.com/engine/
+[Docker Model Runner requirements]: https://docs.docker.com/ai/model-runner/
+[Docker Offload]: https://www.docker.com/products/docker-offload/

adk-cerebras/README.md

@@ -1,31 +1,39 @@
 # DevDuck agents
 
-A multi-agent system for Go programming assistance built with Google Agent Development Kit (ADK). This project features a coordinating agent (DevDuck) that manages two specialized sub-agents (Bob and Cerebras) for different programming tasks.
+A multi-agent system for Go programming assistance built with Google Agent Development Kit (ADK). This
+project features a coordinating agent (DevDuck) that manages two specialized sub-agents (Bob and
+Cerebras) for different programming tasks.
 
 ## Architecture
 
-The system consists of three main agents orchestrated by Docker Compose, which plays a **primordial role** in launching and coordinating all agent services:
+The system consists of three main agents orchestrated by Docker Compose, which plays a
+**primordial role** in launching and coordinating all agent services:
 
 ### 🐙 Docker Compose Orchestration
+
 - **Central Role**: Docker Compose serves as the foundation for the entire multi-agent system
 - **Service Orchestration**: Manages the lifecycle of all three agents (DevDuck, Bob, and Cerebras)
-- **Configuration Management**: Defines agent prompts, model configurations, and service dependencies directly in the compose file
+- **Configuration Management**: Defines agent prompts, model configurations, and service dependencies
+  directly in the compose file
 - **Network Coordination**: Establishes secure inter-agent communication channels
 - **Environment Management**: Handles API keys, model parameters, and runtime configurations
 
-### Agent Components:
+### Agent Components
 
 ### 🦆 DevDuck (Main Agent)
+
 - **Role**: Main development assistant and project coordinator
 - **Model**: Qwen3 (unsloth/qwen3-gguf:4B-UD-Q4_K_XL)
 - **Capabilities**: Routes requests to appropriate sub-agents based on user needs
 
 ### 👨‍💻 Bob Agent
+
 - **Role**: General development tasks and project coordination
 - **Model**: Qwen2.5 (ai/qwen2.5:latest)
 - **Specialization**: Go programming expert for understanding code, explaining concepts, and generating code snippets
 
 ### 🧠 Cerebras Agent
+
 - **Role**: Advanced computational tasks and complex problem-solving
 - **Model**: Llama-4 Scout (llama-4-scout-17b-16e-instruct)
 - **Provider**: Cerebras API
@@ -43,21 +51,25 @@ The system consists of three main agents orchestrated by Docker Compose, which p
 
 ### Prerequisites
 
-+ **[Docker Desktop](https://www.docker.com/products/docker-desktop/) 4.43.0+ or [Docker Engine](https://docs.docker.com/engine/)** installed
-+ **A laptop or workstation with a GPU** (e.g., a MacBook) for running open models locally. If you don't have a GPU, you can alternatively use [**Docker Offload**](https://www.docker.com/products/docker-offload).
-+ If you're using Docker Engine on Linux or Docker Desktop on Windows, ensure that the [Docker Model Runner requirements](https://docs.docker.com/ai/model-runner/) are met (specifically that GPU support is enabled) and the necessary drivers are installed
-+ If you're using Docker Engine on Linux, ensure you have Compose 2.38.1 or later installed
+- **[Docker Desktop] 4.43.0+ or [Docker Engine]** installed.
+- **A laptop or workstation with a GPU** (e.g., a MacBook) for running open models locally. If you
+  don't have a GPU, you can alternatively use **[Docker Offload]**.
+- If you're using [Docker Engine] on Linux or [Docker Desktop] on Windows, ensure that the
+  [Docker Model Runner requirements] are met (specifically that GPU
+  support is enabled) and the necessary drivers are installed.
+- If you're using Docker Engine on Linux, ensure you have [Docker Compose] 2.38.1 or later installed.
 
 ### Configuration
 
-1. **You need a Cerebras API Key**: https://cloud.cerebras.ai/
+1. **You need a Cerebras API Key**: <https://cloud.cerebras.ai/>
 2. Create a `.env` file with the following content:
 
 ```env
 CEREBRAS_API_KEY=<your_cerebras_api_key>
 CEREBRAS_BASE_URL=https://api.cerebras.ai/v1
 CEREBRAS_CHAT_MODEL=llama-4-scout-17b-16e-instruct
 ```
+
 > look at the `.env.sample` file
 
 ### ✋ All the prompts are defined in the 🐙 compose file
@@ -71,14 +83,14 @@ docker compose up
 
 The application will be available at [http://0.0.0.0:8000](http://0.0.0.0:8000)
 
-
 ### Usage
 
 The agents can be accessed through the web interface or API endpoints.
 
 > Activate Token Streaming
 
 **You can try this**:
+
 ```text
 Hello I'm Phil
 
@@ -90,20 +102,28 @@ Cerebras can you analyse and comment this code
 
 Can you generate the tests
 ```
+
 > ✋ For a public demo, stay simple, the above examples are working.
 
 **🎥 How to use the demo**: [https://youtu.be/WYB31bzfXnM](https://youtu.be/WYB31bzfXnM)
 
 #### Routing Requests
 
 - **General requests**: Handled by DevDuck, who routes to appropriate sub-agents
-- **Specific agent requests**: 
-  - "I want to speak with Bob" → Routes to Bob agent
-  - "I want to speak with Cerebras" → Routes to Cerebras agent
+- **Specific agent requests**
+  + "I want to speak with Bob" → Routes to Bob agent
+  + "I want to speak with Cerebras" → Routes to Cerebras agent
 
 ## Tips
 
 If for any reason, you cannot go back from the Cerebras agent to the Bob agent, try this:
+
 ```text
 go back to devduck
 ```
+
+[Docker Compose]: https://github.com/docker/compose
+[Docker Desktop]: https://www.docker.com/products/docker-desktop/
+[Docker Engine]: https://docs.docker.com/engine/
+[Docker Model Runner requirements]: https://docs.docker.com/ai/model-runner/
+[Docker Offload]: https://www.docker.com/products/docker-offload/