Harness Skills

Last updated on Mar 9, 2026

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Harness Skills are specialized prompt templates that teach AI coding assistants how to interact with the Harness platform. Each skill encapsulates the domain knowledge needed to accomplish a specific task — generating pipeline YAML, creating services, debugging executions, analyzing costs, and more — so you can work with Harness using natural language in your editor.

Early Preview — Open Source

Harness Skills is available as an Early Preview release. It is fully open source and community feedback is welcome.

• Source Code: github.com/harness/harness-skills

How skills work

Skills are Markdown files with structured instructions that AI editors load as context. When you invoke a skill (e.g., /create-pipeline), the AI reads the skill's instructions and uses the Harness MCP Server tools to execute actions against the Harness platform.

Natural language prompt
    → AI editor loads skill instructions
        → Skill orchestrates MCP tool calls (harness_list, harness_create, etc.)
            → Harness MCP V2 Server
                → Harness Platform APIs

Skills don't embed API schemas directly. Instead, they use the harness_describe MCP tool to discover resource schemas at runtime, keeping skills lightweight and always up to date.

Requirements

• AI coding assistant: Claude Code, Cursor, GitHub Copilot, OpenAI Codex, or Windsurf
• Harness MCP V2 Server: Required for tool execution. See MCP V2 setup
• Harness API Key: Generate an API key

Setup

Claude Code

1. Clone the skills repository and start Claude Code from it:

git clone https://github.com/harness/harness-skills.git
cd harness-skills
claude

2. Configure the Harness MCP V2 server in ~/.claude/settings.json:

{
  "mcpServers": {
    "harness-mcp-v2": {
      "command": "npx",
      "args": ["-y", "harness-mcp-v2"],
      "env": {
        "HARNESS_API_KEY": "<your-api-key>"
      }
    }
  }
}

Skills are auto-discovered from the CLAUDE.md file and the skills/ directory.

Invoke a skill:

/create-pipeline
Create a CI pipeline for a Node.js app that builds, tests, and pushes a Docker image to ECR

Cursor

No manual setup needed — Cursor auto-loads the project rules from .cursor/rules/harness.mdc.

1. Open the harness-skills folder in Cursor.
2. Configure the MCP server in ~/.cursor/mcp.json:

{
  "mcpServers": {
    "harness-mcp-v2": {
      "command": "npx",
      "args": ["-y", "harness-mcp-v2"],
      "env": {
        "HARNESS_API_KEY": "<your-api-key>"
      }
    }
  }
}

3. Reference skills using @file:

@harness-skills/skills/create-pipeline/SKILL.md
Create a CI pipeline for my Go microservice

GitHub Copilot

GitHub Copilot auto-loads instructions from .github/copilot-instructions.md.

1. Open the harness-skills folder in VS Code.
2. Configure the MCP server in .vscode/mcp.json:

{
  "mcpServers": {
    "harness-mcp-v2": {
      "command": "npx",
      "args": ["-y", "harness-mcp-v2"],
      "env": {
        "HARNESS_API_KEY": "<your-api-key>"
      }
    }
  }
}

3. Reference skills using #file:

#file:harness-skills/skills/create-pipeline/SKILL.md
Create a CI/CD pipeline for my Python app

OpenAI Codex

Codex auto-loads the AGENTS.md file as system instructions. Configure the MCP server in your Codex MCP configuration and invoke skills by referencing the skill files.

Available skills

Pipeline and execution

Skill	Description
/create-pipeline	Generate pipeline YAML for CI, CD, or combined workflows with support for approvals, matrix strategies, and multi-stage deployments
/create-pipeline-v1	Generate v1 simplified pipeline YAML (alpha)
/run-pipeline	Execute pipelines, monitor runs, and handle input sets
/debug-pipeline	Analyze execution failures, identify root causes, and suggest fixes
/migrate-pipeline	Convert v0 pipelines to v1 format
/create-trigger	Create webhook, scheduled, and artifact triggers for pipelines
/create-template	Create reusable step, stage, pipeline, and step group templates

Resource management

Skill	Description
/create-service	Define services for Kubernetes, Helm, ECS, Lambda, SSH, and WinRM deployments
/create-environment	Create environments with overrides and configurations
/create-infrastructure	Define infrastructure definitions for target clusters and hosts
/create-connector	Create connectors for Git providers, cloud platforms, container registries, and Kubernetes clusters
/create-secret	Manage secrets including text secrets, secret files, SSH keys, and WinRM credentials

Access control and governance

Skill	Description
/manage-users	Manage users, user groups, and service accounts
/manage-roles	Configure RBAC roles, role assignments, permissions, and resource groups
/manage-feature-flags	Create, list, toggle, and delete feature flags

Platform operations

Skill	Description
/manage-delegates	Monitor delegate health and manage registration tokens

Observability and analysis

Skill	Description
/analyze-costs	Cloud cost analysis, optimization recommendations, and anomaly detection (CCM)
/security-report	Security vulnerability reports, SBOMs, and compliance status (SCS/STO)
/dora-metrics	DORA metrics and engineering performance insights (SEI)
/gitops-status	GitOps application health, sync status, and drift detection
/chaos-experiment	Create and run chaos engineering experiments
/scorecard-review	Service maturity scorecards and compliance checks (IDP)
/audit-report	Audit trails and compliance reports for SOC2, GDPR, and HIPAA
/template-usage	Template dependency tracking and adoption analysis

Governance policies

Skill	Description
/create-policy	Create OPA governance policies for supply chain security

Agents

Skill	Description
/create-agent-template	Generate AI-powered agent templates (metadata, pipeline YAML, and documentation)

Skill anatomy

Each skill lives in skills/<skill-name>/SKILL.md and follows a consistent structure:

skills/create-pipeline/
├── SKILL.md              # Skill definition (required)
└── references/           # Supplementary docs (optional)
    ├── native-steps.md
    ├── v0-pipeline-schema.md
    └── codebase-analysis.md

The SKILL.md file contains:

• Frontmatter — Name, description, version, MCP server dependency, and license metadata
• Instructions — Step-by-step guidance with MCP tool calls and parameters
• Examples — Real invocation scenarios
• Performance notes — Best practices and optimization tips
• Troubleshooting — Common errors and solutions

Reference files in the references/ subdirectory provide supplementary knowledge like schema definitions, decision trees, and template libraries that the AI loads on demand.

Cross-skill workflows

Skills can be chained together for end-to-end workflows. Resources that depend on other resources must be created in the correct order.

New microservice setup

A typical workflow for onboarding a new microservice:

1. /create-connector — Git, Docker registry, and Kubernetes cluster connectors
2. /create-secret — Credentials for connector authentication
3. /create-service — Service definition referencing connectors
4. /create-environment — Target environment configuration
5. /create-infrastructure — Infrastructure definition for the target cluster
6. /create-pipeline — CI/CD pipeline referencing the service, environment, and infrastructure
7. /create-trigger — Webhook or schedule trigger to automate the pipeline

Codebase-aware pipeline generation

The /create-pipeline skill includes codebase analysis capabilities. It can scan your project files to auto-detect:

• Language and runtime from source files (package.json → Node.js, go.mod → Go)
• Build tools from build configuration (Dockerfile, webpack.config.js, pom.xml)
• Test frameworks from test configuration (jest.config.*, pytest.ini)
• Deployment targets from manifests (Chart.yaml → Helm, task-definition.json → ECS)

This allows the skill to generate pipeline YAML tailored to your project without manual configuration.

References

• Harness Skills Repository
• Harness MCP Server
• Contributing Guide