create-pipeline

create-pipeline is a skill for Claude Code, Codex from harness/harness-skills. It costs 119 tokens per session (4,806 once invoked), scanned A, original, Apache-2.0.

A tool for creating Harness pipelines, which are automated workflows for building, testing, and deploying software. It supports continuous integration, continuous delivery, approvals, parallel work, matrix runs, and rollback steps.

In plain words
What is it for?
Use it to create pipelines for builds, tests, container publishing, Kubernetes or Helm deployments, ECS, serverless applications, approvals, and failure recovery.
Why use it?
It converts a project’s build, test, and deployment requirements into a repeatable workflow instead of a manual release process.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create pipelines for builds, tests, container publishing, Kubernetes or Helm deployments, ECS, serverless applications, approvals, and failure recovery.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/harness/harness-skills/create-pipeline
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add harness/harness-skills --skill create-pipeline
Clone the repo
git clone --depth 1 https://github.com/harness/harness-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for create-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/harness/harness-skills/create-pipeline/github.svg)](https://agentmods.dev/skills/harness/harness-skills/create-pipeline)
Your own site
<a href="https://agentmods.dev/skills/harness/harness-skills/create-pipeline"><img src="https://agentmods.dev/badge/skills/harness/harness-skills/create-pipeline/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for create-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/harness/harness-skills/create-pipeline"><img src="https://agentmods.dev/badge/skills/harness/harness-skills/create-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,806 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Prompt Injection · line 38
    Subtle instructions detected that may alter agent decision-making or introduce hidden biases.
    Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
  • medium Data Exfiltration · line 45
    Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.
    Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00119 $0.04806
Opus 5 $0.00060 $0.02403
Sonnet 5 $0.00024 $0.00961
Haiku 4.5 $0.00012 $0.00481

Measured 10d ago against content hash fcecfa556c78, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

create-pipeline scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Ticketing → use `JiraCreate` / `ServiceNowCreate` (never `Run: curl`)
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/create-pipeline/SKILL.md · 601 lines

How it starts

The opening of the file, as written. The whole thing — 601 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Pipeline

Generate Harness v0 Pipeline YAML and optionally push to Harness via MCP.

Instructions

  1. Analyze codebase (if source code is available) - Scan the project to auto-detect language, build tools, test frameworks, containerization, deployment manifests, and target infrastructure. Use the detection tables and decision tree in references/codebase-analysis.md to determine:
    • Language and runtime version (package.json → Node.js, go.mod → Go, pom.xml → Java, etc.)
    • Build commands and base images
    • Test framework and report format (Jest → JUnit, pytest → JUnit XML, etc.)
    • Linter and formatter (ESLint, Prettier, Ruff, etc.)
    • Dockerfile presence and registry type (Docker Hub, ECR, GCR, ACR)
    • Deployment manifests → Harness service/deployment type (k8s manifests → Kubernetes, Chart.yaml → NativeHelm, task-definition.json → ECS, serverless.yml → ServerlessAwsLambda)
    • Existing CI/CD configs for migration (GitHub Actions, Jenkins, GitLab CI, etc.)
  2. Clarify requirements - Confirm detected settings with the user. Ask about anything that couldn't be auto-detected — do not guess or use placeholders. If the user's request is ambiguous, ask before generating YAML. Examples of what to ask when missing:
    • Deployment target / infrastructure: region (e.g. us-east-1), cluster name or ID, account ID (e.g. AWS account for ECR/ECS)
    • Registry: which registry (Docker Hub, ECR, GCR, ACR), registry identifier/URL, repo path
    • Cloud provider: which account, region, and resource identifiers for connectors/infrastructure
    • Approval gates, notification channels if relevant Critical rule: Never hardcode placeholder values (e.g. 123456789012, us-east-1, my-cluster) for deployment target, region, registry, or cluster when the user did not specify them — ask the user instead. If the user did not specify region, account ID, cluster, or registry (e.g. "deploys to ECS" with no region or cluster), ask the user for those values before generating YAML.
  3. Select native steps - Always prefer Harness native steps over Run or ShellScript steps. Consult references/native-steps.md for the full mapping. Key rules:
    • Docker build/push → use BuildAndPushDockerRegistry / BuildAndPushECR / BuildAndPushGCR / BuildAndPushACR (never Run: docker build && docker push)
    • K8s deploy → use K8sRollingDeploy / K8sBlueGreenDeploy / K8sCanaryDeploy (never Run: kubectl apply)
    • Helm deploy → use HelmDeploy (never Run: helm upgrade --install)
    • ECS deploy → use EcsRollingDeploy (never Run: aws ecs update-service)
    • Terraform → use TerraformPlan / TerraformApply (never Run: terraform apply)
    • Security scanning → use native STO steps (AquaTrivy, Snyk, Sonarqube, Semgrep, etc.)
    • Uploads → use S3Upload / GCSUpload (never Run: aws s3 cp)
    • Approvals → use HarnessApproval / JiraApproval (never polling scripts)
    • Ticketing → use JiraCreate / ServiceNowCreate (never Run: curl)
    • Use Run steps only for custom build/test/lint commands with no native equivalent
    • Test steps: Any Run step that runs unit or integration tests must include a reports block (e.g. type: JUnit, spec.paths) so Harness can capture results; see references/codebase-analysis.md for framework → report path.
  4. Generate valid YAML following the structure below, using the detected build/test/deploy commands. Validation rules: (a) Stage names must match ^[a-zA-Z_0-9-.][-0-9a-zA-Z_\\s.]{0,127}$ — use only letters, numbers, spaces, hyphens, underscores, or periods (no commas). (b) Every CI and CD stage must include a failureStrategies array (Approval stages do not require one). For CI use MarkAsFailure (never Ignore — it hides failures); for CD use StageRollback.
  5. Optionally create via MCP — First verify the project exists (see "Creating via MCP" section below), then use harness_create with resource_type pipeline and body: { yamlPipeline: "<YAML string>" }

Read the full file on GitHub · 601 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 601 lines · 119 tokens per session scan A fcecfa556c78

Subscribe to this mod's changes

create-pipeline is a skill published in the GitHub repository harness/harness-skills (105 stars, last pushed today), licensed Apache-2.0. It adds 119 tokens to every session and 4,806 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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