Skip to main content

What is Prometheus?

Prometheus is an intelligent planning agent that helps you think through complex work via an interactive interview process. It’s read-only—can only create or modify markdown files within .sisyphus/.
Think of Prometheus as a strategic consultant who helps you articulate exactly what you need before anyone starts building.

Why Use Prometheus?

ScenarioWithout PrometheusWith Prometheus
Scope creepAgent adds unasked featuresClear boundaries defined upfront
Missing edge casesDiscovered during implementationIdentified in planning phase
Unclear requirementsAgent guesses, gets it wrongInterviewing clarifies intent
Wasted workBuild wrong thing, start overBuild right thing first time

Quick Start

1

Invoke Prometheus

Method 1: Switch agent (Tab → Select Prometheus)Method 2: Use @plan command (stays in current session)
@plan "Refactor the authentication system to support OAuth"
2

Answer interview questions

Prometheus will ask clarifying questions:
Prometheus: What providers should OAuth support? (Google, GitHub, etc.)

Prometheus: Should existing password auth remain available?

Prometheus: Are there specific security requirements?
Answer thoroughly. Prometheus uses your answers to build the plan.
3

Review generated plan

Plan is saved to .sisyphus/plans/{name}.md
# OAuth Authentication Refactor

## Objective
Add OAuth 2.0 support while maintaining existing password auth...

## Scope
IN SCOPE:
- Google OAuth integration
- GitHub OAuth integration
- User account linking

OUT OF SCOPE:
- Social provider APIs beyond auth
- Migration of existing accounts

## Implementation Plan
...
4

Execute plan

/start-work
Atlas reads the plan and executes systematically.

How Prometheus Works

The Interview Process

Intent-Specific Strategies

Prometheus adapts questions based on what you’re doing:
Focus: Safety and behavior preservationQuestions:
  • What tests verify current behavior?
  • What must NOT change?
  • Rollback strategy if issues arise?
  • Performance requirements?
Plan emphasis:
  • Behavior preservation checkpoints
  • Incremental refactoring steps
  • Verification after each step

The Three Agents

Prometheus (Planner)

Model: Claude Opus 4.6 (with extended thinking)
Role: Strategic consultant and interviewer
Capabilities:
  • Launches explore/librarian agents to gather context
  • Asks clarifying questions iteratively
  • Detects when requirements are sufficiently clear
  • Generates structured implementation plans
Restrictions:
  • Read-only outside .sisyphus/ directory
  • Can only create/modify .md files in .sisyphus/plans/
  • Cannot execute code or make changes

Metis (Plan Consultant)

Model: Claude Opus 4.6
Role: Gap analyzer and critic
Called automatically before Prometheus writes the final plan. What Metis checks:
  • Hidden intentions in user’s request
  • Ambiguities that could derail implementation
  • AI failure patterns (over-engineering, scope creep)
  • Missing acceptance criteria
  • Edge cases not addressed
Why Metis exists:
The plan author (Prometheus) has “ADHD working memory”—it makes connections that never make it onto the page. Metis forces externalization of implicit knowledge.

Momus (Plan Reviewer)

Model: GPT-5.2
Role: Ruthless reviewer for high-accuracy mode
Activated when user opts into high-accuracy mode. Momus only says “OKAY” when:
  • 100% of file references verified
  • ≥80% of tasks have clear reference sources
  • ≥90% of tasks have concrete acceptance criteria
  • Zero tasks require assumptions about business logic
  • Zero critical red flags
If REJECTED: Prometheus fixes issues and resubmits. No maximum retry limit.
Momus is strict. High-accuracy mode takes longer but produces battle-tested plans.

Using Prometheus

Method 1: Switch Agent

1

Switch to Prometheus

Press Tab at the promptSelect “Prometheus” from agent list
2

Describe your work

I want to refactor the auth system to support OAuth providers
3

Answer questions

Prometheus interviews you to clarify requirements
4

Plan is generated

Saved to .sisyphus/plans/{name}.md

Method 2: Use @plan Command

Stay in current session (usually Sisyphus):
@plan "Implement rate limiting for all API endpoints"
The @plan command automatically switches context to Prometheus, runs the planning flow, then returns.

Which Method?

Use CaseRecommended
New session, starting freshSwitch to Prometheus agent
Already mid-workUse @plan command
Want explicit controlSwitch to Prometheus agent
Quick planning interruptUse @plan command
Both methods trigger identical planning behavior. Use whichever feels natural.

Plan Structure

Prometheus-generated plans follow a consistent structure:
---
generated: 2026-03-01
agent: prometheus
status: ready
---

# {Plan Title}

## Objective
Clear, measurable goal statement

## Background
Context: why this work, what led to it, current state

## Scope
### IN SCOPE
- Specific deliverable 1
- Specific deliverable 2

### OUT OF SCOPE
- Thing we explicitly won't do
- Future work deferred

## Requirements
### Functional
- Requirement 1 with acceptance criteria
- Requirement 2 with acceptance criteria

### Non-Functional
- Performance targets
- Security requirements
- Compatibility requirements

## Implementation Plan
### Phase 1: {Name}
**Goal:** What this phase achieves

**Tasks:**
1. **Task name** [`file/path.ts:123`]
   - Specific action
   - How to verify
   - References to existing patterns

### Phase 2: {Name}
...

## Testing Strategy
- Unit test coverage requirements
- Integration test scenarios
- Manual verification steps

## Verification Checklist
- [ ] All acceptance criteria met
- [ ] Tests pass
- [ ] No new lint/type errors
- [ ] Documentation updated

## Risks and Mitigations
| Risk | Impact | Mitigation |
|------|--------|------------|

## Reference Materials
- Link to relevant docs
- Existing implementation patterns
- External resources

High Accuracy Mode

For critical work, enable Momus review:
1

Generate plan normally

Complete the Prometheus interview process
2

Request high accuracy

When Prometheus presents the plan:
User: Use high accuracy mode
or
User: Have Momus review this
3

Momus review loop

Momus validates against strict criteria:OKAY → Plan approved, ready to execute
REJECTED → Prometheus fixes issues and resubmits
Momus: REJECTED

Issues found:
1. Task 3 lacks file reference - which file contains the auth middleware?
2. Phase 2 acceptance criteria too vague - what specifically validates "working"?
3. Missing edge case: what happens if OAuth provider is down?

Resubmit after addressing these issues.
4

Iterate until OKAY

Prometheus fixes issues, Momus reviews again. Continues until approval.
High accuracy mode is slower but produces plans that rarely need revision during execution.

Executing Plans: /start-work

What /start-work Does

1

Checks for existing work

.sisyphus/boulder.json exists?
  YES Resume existing plan
  NO Start new plan
2

Finds the plan

Uses most recent plan in .sisyphus/plans/
3

Switches to Atlas

Atlas (the conductor) reads the plan
4

Executes systematically

Atlas works through tasks, delegating to specialists

Session Continuity

Boulder state (.sisyphus/boulder.json) tracks:
  • active_plan: Path to current plan file
  • session_ids: All sessions working on this plan
  • started_at: When work began
  • plan_name: Human-readable identifier
Example timeline:
Monday 9:00 AM
  → @plan "Build user authentication"
  → Prometheus creates plan
  → /start-work
  → Atlas starts execution, creates boulder.json
  → Task 1 complete, Task 2 in progress...
  → [Session crashes]

Monday 2:00 PM (NEW SESSION)
  → User opens new session
  → /start-work
  → [Hook reads boulder.json]
  → "Resuming 'Build user authentication' - 3 of 8 tasks complete"
  → Atlas continues from Task 3
No context is lost across sessions. Atlas picks up exactly where it left off.

Configuration

{
  "sisyphus_agent": {
    "planner_enabled": true,      // Enable/disable Prometheus
    "replace_plan": true          // Demote default planner
  },
  
  "agents": {
    "prometheus": {
      "model": "anthropic/claude-opus-4-6",
      "thinking": {
        "type": "enabled",
        "budgetTokens": 32000       // Extended thinking for planning
      },
      "prompt_append": "Leverage deep & quick agents heavily, always in parallel."
    },
    
    "metis": {
      "model": "anthropic/claude-opus-4-6"
    },
    
    "momus": {
      "model": "openai/gpt-5.2"    // Different perspective from GPT
    }
  },
  
  "disabled_hooks": [
    // "prometheus-md-only"  // Remove write restrictions (not recommended)
  ]
}

Real-World Examples

Example 1: Complex Refactor

Prompt:
@plan "Migrate from REST to GraphQL while maintaining REST compatibility"
Interview:
Prometheus: Which endpoints should be migrated first? All at once or phased?
User: Phased. Start with user endpoints.

Prometheus: Should REST remain indefinitely or have a deprecation timeline?
User: Deprecation in 6 months, full removal in 12 months.

Prometheus: What GraphQL schema design patterns exist in the codebase?
User: None yet, this is the first GraphQL work.

Prometheus: [Launches explore agent to find similar projects]
Generated plan:
  • Phase 1: GraphQL server setup
  • Phase 2: User endpoint migration
  • Phase 3: Parallel operation period (6mo)
  • Phase 4: Deprecation warnings
  • Phase 5: REST removal
Each phase has specific tasks, file references, and verification steps.

Example 2: New Feature

Prompt:
@plan "Add real-time notifications with WebSockets"
Interview:
Prometheus: What events should trigger notifications?
User: New messages, mentions, system alerts.

Prometheus: Should notifications persist when user is offline?
User: Yes, store in database and send when they reconnect.

Prometheus: Found existing Redis pub/sub setup. Use that for broadcasting?
User: Yes, perfect.
Generated plan:
  • WebSocket server setup (uses existing Redis)
  • Event subscription system
  • Offline notification storage
  • Client reconnection handling
  • Testing strategy for connection drops

Example 3: Architecture Decision

Prompt:
@plan "Design caching layer for high-traffic API"
Interview:
Prometheus: Expected request volume?
User: 10k req/sec peak, 2k avg.

Prometheus: Read-heavy or write-heavy?
User: 90% reads, 10% writes.

Prometheus: Consistency requirements? Eventual consistency acceptable?
User: 5-second staleness acceptable for most data.

Prometheus: [Consults Oracle agent for architecture recommendations]
Generated plan:
  • Redis cache layer (95% hit rate target)
  • Cache invalidation strategy
  • Fallback to database
  • Monitoring and metrics
  • Gradual rollout (10% → 50% → 100%)

Troubleshooting

Cause: Requirements genuinely unclear.Solution: Answer questions thoroughly. Prometheus stops when it has enough clarity. Or explicitly say:
I've provided enough detail. Generate the plan with what you have.
Cause: Prometheus inferred incorrectly.Solution: Enable high-accuracy mode:
Use high accuracy mode
Momus will catch and force correction of invalid references.
Cause: No plans in .sisyphus/plans/ or boulder.json points elsewhere.Solution:
# Create plan first
@plan "Your task description"

# Or delete stale boulder.json
rm .sisyphus/boulder.json
/start-work
Cause: Plan may be too vague or missing context.Solution:
  • Use high-accuracy mode next time
  • Add more specific task descriptions
  • Include file references for each task
  • Provide examples of desired patterns

Tips for Best Results

Be specific about constraints

✅ "Must maintain <100ms response time"
❌ "Should be fast"

Mention existing patterns

✅ "Follow the pattern in src/services/user.ts"
❌ "Implement user service"

Define success clearly

✅ "Success: All tests pass, no type errors, <5% perf regression"
❌ "Success: It works"

State what NOT to do

✅ "Do NOT modify the existing API contracts"
❌ (Assume agent will figure it out)

Combining with Other Features

Prometheus + Ultrawork

# Plan with Prometheus
@plan "Build admin dashboard with analytics"

# Execute with ultrawork intensity
/start-work
# Then type: ulw
Atlas reads the plan and uses ultrawork-style delegation automatically.

Prometheus + Ralph Loop

For persistent execution:
@plan "Implement payment integration"
/ralph-loop "/start-work"
Ralph keeps pushing until the plan is fully executed.

Commands

Learn about /start-work and other commands

Background Agents

How Atlas delegates work in parallel

Agent Model Matching

Why Prometheus uses Claude Opus

Ultrawork Mode

Maximum intensity execution

Build docs developers (and LLMs) love