| name | workflows-expert |
| description | 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". |
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 get_workflow_info 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 successfullyfailure- Workflow failed (checkerrorfield)paused- Workflow paused for user input (useresume_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
get_workflow_info(workflow, format) - Get detailed workflow metadata
- Shows inputs, outputs, blocks, dependencies
- Call before executing
Execution
execute_workflow(workflow, inputs, response_format) - Execute registered workflow
- Provide required inputs from
get_workflow_info - Use
response_format: 'minimal'(default) or'detailed'(debugging only)
execute_inline_workflow(workflow_yaml, inputs, response_format) - Execute YAML directly
- For one-off or custom workflows
- Validate first with
validate_workflow_yaml
validate_workflow_yaml(yaml_content) - Validate workflow before execution
- Catches syntax errors early
- Always validate inline workflows
Checkpoint Management
resume_workflow(checkpoint_id, response, response_format) - Resume paused workflow
- For interactive workflows with Prompt blocks
- Provide user response to continue
list_checkpoints(workflow_name, format) - View saved checkpoints
get_checkpoint_info(checkpoint_id, format) - Inspect checkpoint details
delete_checkpoint(checkpoint_id) - Clean up old checkpoints
Variable Syntax Quick Reference
All variables use four-namespace architecture:
Inputs: {{inputs.project_name}}, {{inputs.workspace}}
Metadata: {{metadata.workflow_name}}, {{metadata.start_time}}
Blocks: {{blocks.run_tests.outputs.exit_code}}, {{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
- Use tag-based discovery - Call
list_workflows(tags=[...])instead of guessing names - Inspect before executing - Call
get_workflow_info()to understand requirements - Use status shortcuts - Prefer
.succeededover.outputs.exit_code == 0 - Minimal response format - Use
response_format='minimal'unless debugging - Validate inline workflows - Use
validate_workflow_yaml()beforeexecute_inline_workflow() - 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`
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`
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
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 execute_inline_workflow 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:
- Tag-based discovery - Find workflows by purpose
- Workflow inspection - Understand requirements before execution
- DAG-based execution - Automatic dependency resolution and parallel execution
- Conditional logic - Boolean shortcuts for clean conditions
- Workflow composition - Build complex pipelines from reusable workflows
Key Pattern
Always follow: Discover → Inspect → Execute