بنقرة واحدة
brain-dump-workflow
Enforces Brain Dump quality workflow for ticket implementation with automatic telemetry
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Enforces Brain Dump quality workflow for ticket implementation with automatic telemetry
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Update Brain Dump's AI model pricing catalog (DEFAULT_COST_MODELS) when providers release new models or change prices. Use when the user asks to add a new model, refresh provider pricing, or fix ticket cost attribution for a model that shows $0 or wrong costs. Covers Anthropic, OpenAI, Google, Cursor, OpenCode, and open-source providers.
Use this skill when Ralph is working autonomously through Brain Dump backlogs. Covers ticket selection, implementation patterns, and autonomous workflow management.
MANDATORY quality workflow for Brain Dump tickets. Defines the exact MCP tool call sequence every ticket must follow. Load this before starting any ticket work.
Autonomous backlog processing workflow for Brain Dump using the Universal Quality Workflow. Use when working through multiple tickets autonomously or when asked to process a backlog like Ralph.
MANDATORY quality workflow for Brain Dump tickets. Defines the exact MCP tool call sequence every ticket must follow. Load this before starting any ticket work.
Review Brain Dump ticket work using CLI commands only. Use when implementation is finished and findings, fixes, and demo generation need to be tracked without MCP.
| name | brain-dump-workflow |
| description | Enforces Brain Dump quality workflow for ticket implementation with automatic telemetry |
This skill guides you through the Brain Dump quality workflow, ensuring consistent code quality and proper tracking across all AI-assisted development.
Brain Dump implements a structured quality workflow inspired by Dillon Mulroy's "tracer review" pattern:
ready → in_progress → ai_review → human_review → done
Each phase has specific requirements and MCP tools to use.
When you begin working on a ticket:
// 1. Start the ticket work (creates git branch, updates status)
mcp__brain-dump__workflow "start-work"({ ticketId: "<ticket-id>" })
// 2. Create a session for state tracking
mcp__brain-dump__session "create"({ ticketId: "<ticket-id>" })
// Returns: { sessionId: "..." }
// 3. Update state as you progress
mcp__brain-dump__session "update-state"({
sessionId: "<session-id>",
state: "analyzing",
metadata: { message: "Reading ticket requirements" }
})
Update your state as you work through phases:
| State | When to use |
|---|---|
analyzing | Reading and understanding requirements |
implementing | Writing or modifying source code |
testing | Running tests to verify behavior |
committing | Creating git commits |
reviewing | Final self-review before completing |
Example:
mcp__brain-dump__session "update-state"({
sessionId: "<session-id>",
state: "implementing",
metadata: { message: "Adding new API endpoint" }
})
When implementation is done:
// 1. Run validation discovered from this project's docs/config.
// Do not assume pnpm/npm; use the project-standard commands.
// 2. Complete the ticket work
mcp__brain-dump__workflow "complete-work"({
ticketId: "<ticket-id>",
summary: "Added new API endpoint with validation and tests"
})
// Status becomes: ai_review
During AI review, run code review agents:
// Submit findings from review
mcp__brain-dump__review "submit-finding"({
ticketId: "<ticket-id>",
agent: "code-reviewer",
severity: "major",
category: "error-handling",
description: "Missing error handling for null input"
})
// After fixing, mark as fixed
mcp__brain-dump__review "mark-fixed"({
findingId: "<finding-id>",
fixStatus: "fixed",
fixDescription: "Added null check at line 45"
})
// Check if all critical/major issues are resolved
mcp__brain-dump__review "check-complete"({ ticketId: "<ticket-id>" })
// Returns: { canProceedToHumanReview: true/false }
When AI review passes (all critical/major findings fixed):
mcp__brain-dump__review "generate-demo"({
ticketId: "<ticket-id>",
steps: [
{ order: 1, description: "Navigate to /settings", expectedOutcome: "Settings page loads", type: "manual" },
{ order: 2, description: "Click 'Add User' button", expectedOutcome: "Modal appears", type: "visual" },
{ order: 3, description: "Submit form with valid data", expectedOutcome: "Success message shown", type: "manual" }
]
})
// Status becomes: human_review
After generating the demo script, STOP. Do not attempt to auto-approve the ticket.
The human reviewer will:
mcp__brain-dump__review "submit-feedback"() with their verdictdone only after human approvalAll your tool usage is automatically captured by the telemetry hooks:
This provides full audit trails for enterprise compliance.
| Action | MCP Tool |
|---|---|
| Start ticket | workflow "start-work"({ ticketId }) |
| Create session | session "create"({ ticketId }) |
| Update state | session "update-state"({ sessionId, state }) |
| Complete work | workflow "complete-work"({ ticketId, summary }) |
| Submit finding | review "submit-finding"({ ticketId, agent, severity, category, description }) |
| Fix finding | review "mark-fixed"({ findingId, fixStatus }) |
| Check review | review "check-complete"({ ticketId }) |
| Generate demo | review "generate-demo"({ ticketId, steps }) |