smithery.ai

workflows-expert

Activate when requests involve workflow execution, CI/CD pipelines, git automation, or multi-step task orchestration.

First seen Apr 2, 2026

Installation

$ npx skills add https://smithery.ai

Summary

  • Activate when requests involve workflow execution, CI/CD pipelines, git automation, or multi-step task orchestration.
  • This skill provides workflows-mcp MCP server integration with tag-based workflow discovery, DAG-based execution, and variable syntax expertise.
  • Trigger on phrases like "run workflow", "execute workflow", "orchestrate tasks", "automate CI/CD", or "workflow information".

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from smithery.ai · top by installs.

npx skills add https://smithery.ai

Browse all from smithery.ai

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 8,155 B
  • docs SUMMARY.md 411 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Workflows MCP Expert Skill

Activate when requests involve workflow execution, multi-step task orchestration, or CI/CD automation using the workflows-mcp MCP server.

Activation Triggers

Activate when user requests mention:

  • "run workflow", "execute workflow", "list workflows"
  • "orchestrate tasks", "multi-step process", "DAG execution"
  • "CI/CD pipeline", "git automation", "automated testing"
  • "workflow information", "workflow details"
  • Task coordination with dependencies
  • "Chain commands", "automate workflow"

Common user phrases: "run tests before deploying", "create build pipeline", "execute only if previous succeeds", "run tasks in parallel"

Core Workflow Pattern

Standard execution: Discover → Inspect → Execute

Always use tag-based discovery instead of guessing workflow names. Inspect workflows before execution to understand required inputs.

Step 1: Discover by Tags

Use list_workflows with tags (AND logic - workflows must have ALL tags):

Tool: list_workflows
Parameters:
  tags: ['python', 'ci']
  format: 'markdown'

Common tag combinations:

  • Python: ['python'], ['python', 'testing'], ['python', 'ci']
  • Git: ['git'], ['git', 'commit'], ['git', 'checkout']
  • CI/CD: ['ci'], ['ci', 'deployment']
  • TDD: ['tdd'], ['tdd', 'phase1']

Step 2: Inspect Workflow

Call getworkflowinfo before executing to understand inputs, outputs, and structure:

Tool: get_workflow_info
Parameters:
  workflow: 'python-ci-pipeline'
  format: 'markdown'

Step 3: Execute Workflow

Tool: execute_workflow
Parameters:
  workflow: 'python-ci-pipeline'
  inputs: {project_path: '/path/to/project'}
  response_format: 'minimal'

Response status values:

  • success - Workflow completed successfully
  • failure - Workflow failed (check error field)
  • paused - Workflow paused for user input (use resume_workflow)

Available MCP Tools

Discovery & Information

list_workflows(tags, format) - Discover workflows by tags

  • Filter with AND logic: tags=['python', 'testing']
  • Returns workflow names only

getworkflowinfo(workflow, format) - Get detailed workflow metadata

  • Shows inputs, outputs, blocks, dependencies
  • Call before executing

Execution

executeworkflow(workflow, inputs, responseformat) - Execute registered workflow

  • Provide required inputs from getworkflowinfo
  • Use response_format: 'minimal' (default) or 'detailed' (debugging only)

executeinlineworkflow(workflowyaml, inputs, responseformat) - Execute YAML directly

  • For one-off or custom workflows
  • Validate first with validateworkflowyaml

validateworkflowyaml(yaml_content) - Validate workflow before execution

  • Catches syntax errors early
  • Always validate inline workflows

Checkpoint Management

resumeworkflow(checkpointid, response, response_format) - Resume paused workflow

  • For interactive workflows with Prompt blocks
  • Provide user response to continue

listcheckpoints(workflowname, format) - View saved checkpoints

getcheckpointinfo(checkpoint_id, format) - Inspect checkpoint details

deletecheckpoint(checkpointid) - Clean up old checkpoints

Variable Syntax Quick Reference

All variables use four-namespace architecture:

Inputs: {{inputs.project_name}}, {{inputs.workspace}}

Metadata: {{metadata.workflowname}}, {{metadata.starttime}}

Blocks: {{blocks.runtests.outputs.exitcode}}, {{blocks.test.succeeded}}

Status shortcuts (use for 90% of conditionals):

  • {{blocks.test.succeeded}} - True if completed successfully
  • {{blocks.build.failed}} - True if failed
  • {{blocks.optional.skipped}} - True if skipped

For detailed variable syntax, load ./references/variable-syntax.md.

Essential Patterns

Conditional Execution

blocks:
  - id: run_tests
    type: Shell
    inputs:
      command: pytest tests/

  - id: deploy
    type: Shell
    inputs:
      command: ./deploy.sh
    condition: "{{blocks.run_tests.succeeded}}"
    depends_on: [run_tests]

Workflow Composition

blocks:
  - id: ci_pipeline
    type: Workflow
    inputs:
      workflow: "python-ci-pipeline"
      inputs:
        project_path: "{{inputs.workspace}}"

Parallel Execution

Blocks without dependencies run in parallel automatically.

Best Practices

  1. Use tag-based discovery - Call list_workflows(tags=[...]) instead of guessing names
  2. Inspect before executing - Call getworkflowinfo() to understand requirements
  3. Use status shortcuts - Prefer .succeeded over .outputs.exit_code == 0
  4. Minimal response format - Use response_format='minimal' unless debugging
  5. Validate inline workflows - Use validateworkflowyaml() before executeinlineworkflow()
  6. Explicit namespaces - Always use inputs., blocks., metadata.*

Reference Documentation

Load these files as needed using the Read tool:

Variable Syntax Reference

[./references/variable-syntax.md](./references/variable-syntax.md)

Load when: Resolving variable syntax errors, understanding namespace architecture, debugging variable resolution, or learning advanced patterns.

Contains: Complete variable resolution rules, recursive resolution, cross-block references, common mistakes, debugging techniques.

Block Executors Reference

[./references/block-executors.md](./references/block-executors.md)

Load when: Understanding available block types (Shell, Workflow, CreateFile, ReadFile, etc.), checking input/output specs, learning execution patterns, troubleshooting block issues.

Contains: Complete block type reference, input/output specifications, execution states, status vs outcome distinction, patterns and troubleshooting.

Complete Workflow Examples

[./references/examples.md](./references/examples.md)

Load when: Implementing complex multi-stage workflows, building parallel execution pipelines, creating file processing workflows, designing interactive approval workflows, learning advanced patterns.

Contains: Full workflow examples with documentation, multi-stage deployments, parallel testing with aggregation, file processing pipelines, interactive deployments.

Example Workflow Templates

Directory: ./examples/

Available templates:

  • ./examples/simple-ci-pipeline.yaml - Basic CI pipeline with sequential execution
  • ./examples/conditional-deploy.yaml - Environment-based deployment with conditions
  • ./examples/parallel-testing.yaml - Parallel test execution with result aggregation

Usage: Copy and modify YAML templates for custom workflows. Execute using executeinlineworkflow tool.

Troubleshooting Quick Guide

Variable errors: Verify namespace (inputs., blocks., metadata.*), check block ID case-sensitivity, ensure depends_on for output references

Execution failures: Check error field, use response_format: "detailed" for debugging, verify required inputs, validate condition syntax

Workflow not found: Use list_workflows() to see available workflows, check name spelling (case-sensitive), verify MCP connection

Summary

The workflows-mcp server enables workflow orchestration through:

  1. Tag-based discovery - Find workflows by purpose
  2. Workflow inspection - Understand requirements before execution
  3. DAG-based execution - Automatic dependency resolution and parallel execution
  4. Conditional logic - Boolean shortcuts for clean conditions
  5. Workflow composition - Build complex pipelines from reusable workflows

Key Pattern

Always follow: Discover → Inspect → Execute