feat: launch Vibeflow n8n v0.5.0

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Felipe Domingues 2026-04-12 13:33:57 -03:00
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# Architecture
## Purpose
Vibeflow n8n is a skill-first architecture for building complete n8n workflows through MCP-capable coding agents.
It is not a standalone runtime.
It is a reusable behavioral layer that can be attached to different agent clients.
## High-level components
### 1. User
The human describes the automation goal in natural language.
### 2. Agent client
A CLI or coding assistant that supports:
- custom instructions / skills,
- MCP connections,
- conversational follow-ups,
- optional local file awareness.
Examples:
- Codex CLI
- Claude Code
- OpenCode
- compatible community forks
### 3. Vibeflow skill layer
This repository provides the skill logic:
- how to interview the user,
- how to normalize requirements,
- how to decide what must be asked,
- how to create a plan,
- how to validate the build,
- how to report completion.
### 4. n8n MCP server
The execution bridge between the agent and n8n.
The skill does not directly manipulate n8n internals.
It relies on the MCP-exposed capabilities available in the connected environment.
### 5. n8n instance
The target automation environment where workflows are created, updated, and later run.
## Core architecture pattern
```text
User intent
-> Conversational intake
-> Normalized plan
-> MCP build actions
-> Validation pass
-> Human-readable handoff
```
## Why planning-first matters
Without a planning step, agents tend to:
- over-assume missing requirements,
- create brittle node graphs,
- hide unresolved credential problems,
- return workflows that are technically created but operationally confusing.
The plan acts like a blueprint before the steel beams go up.
## Build stages
### Stage 1. Intake
The agent captures:
- business goal,
- trigger,
- systems involved,
- desired output,
- rules and exceptions.
### Stage 2. Requirement triage
The agent separates:
- critical unknowns,
- optional detail,
- safe defaults.
### Stage 3. Normalized plan
The agent produces a standard structure for execution.
This makes behavior portable across clients.
### Stage 4. MCP execution
The agent creates or updates the workflow using the available MCP tools.
### Stage 5. Validation
The agent checks for:
- broken graph structure,
- missing dependencies,
- unsupported assumptions,
- absent failure branches,
- unresolved placeholders.
### Stage 6. Delivery
The agent produces a report for the user that is operational, not ornamental.
## Recommended workflow object model
A normalized plan should include:
- workflow_name
- workflow_mode
- business_goal
- trigger
- systems_involved
- steps
- branching_logic
- data_contracts
- credentials_required
- risk_flags
- error_handling
- test_strategy
- assumptions
- open_questions
## Modes
### fast
Prototype-first mode.
Uses more defaults and fewer follow-up questions.
### balanced
Default mode.
Good mix of speed and operational sanity.
### safe
More explicit approvals, stronger validation, fewer silent assumptions.
## Portability strategy
The repository is intentionally text-first.
That means:
- prompts are markdown,
- rules are markdown,
- examples are markdown,
- client-specific notes are lightweight.
This keeps the project easy to adapt across agent ecosystems without locking it to a single vendor format.
## Non-goals
This repository does not try to:
- replace n8n documentation,
- replace the n8n MCP server,
- become a full workflow execution engine,
- hide MCP limitations,
- generate production security posture automatically.
## Future architecture extensions
Potential future additions:
- schema-driven plan JSON
- linter rules for anti-pattern detection
- recipe loader / scenario packs
- test case generator
- workflow diff summarizer
- upgrade assistant for existing workflows