Advanced Prompting Engine

A universal prompt creation engine delivered as an MCP server. Measures intent across 10 philosophical dimensions and returns a construction basis from which the client constructs prompts.

The engine does not generate prompts. It provides the dimensional foundation — active constructs, spectrum opposites, tensions, gems, spokes, and construction questions — that make prompt construction principled rather than heuristic.

Quick Start

# Install
pip install advanced-prompting-engine

# Or run directly via uvx
uvx advanced-prompting-engine

MCP Configuration

Add to your .mcp.json:

{
  "mcpServers": {
    "advanced-prompting-engine": {
      "command": "uvx",
      "args": ["advanced-prompting-engine"]
    }
  }
}

What It Does

The engine positions your intent in a 10-dimensional philosophical manifold:

Branch	Sub-dimensions
Ontology	Particular ↔ Universal, Static ↔ Dynamic
Epistemology	Empirical ↔ Rational, Certain ↔ Provisional
Axiology	Intrinsic ↔ Instrumental, Individual ↔ Collective
Teleology	Immediate ↔ Ultimate, Intentional ↔ Emergent
Phenomenology	Objective ↔ Subjective, Surface ↔ Deep
Praxeology	Individual ↔ Coordinated, Reactive ↔ Proactive
Methodology	Analytic ↔ Synthetic, Deductive ↔ Inductive
Semiotics	Explicit ↔ Implicit, Syntactic ↔ Semantic
Hermeneutics	Literal ↔ Figurative, Author-intent ↔ Reader-response
Heuristics	Systematic ↔ Intuitive, Conservative ↔ Exploratory

Each branch is a 10x10 grid of 100 epistemic observation points. Position determines classification (corner/midpoint/edge/center), potency, and spectrum membership. The engine computes tensions, gems (inter-branch integrations), spokes (per-branch behavioral signatures), and a central gem coherence score.

Tools

Tool	Purpose
create_prompt_basis	Primary — intent or coordinate in, construction basis out
explore_space	Expert — graph traversal, stress testing, triangulation
extend_schema	Authoring — add constructs and relations with contradiction detection

Example

# Pre-formed coordinate — place each branch precisely
coordinate = {
    "ontology": {"x": 0, "y": 0, "weight": 1.0},      # corner: particular + static
    "epistemology": {"x": 1, "y": 0, "weight": 0.8},    # edge: empirical + certain
    "methodology": {"x": 0, "y": 0, "weight": 0.8},     # corner: analytic + deductive
    "teleology": {"x": 8, "y": 0, "weight": 0.9},       # edge: near-ultimate + intentional
    # ... all 10 branches
}

# Returns: active constructs, spectrum opposites, tensions,
# gems, spokes, central gem, and 10 construction questions
result = create_prompt_basis(coordinate=coordinate)

The construction basis tells you what your prompt assumes exists (ontology), how it establishes truth (epistemology), what it values (axiology), what it's directed toward (teleology), and so on — each with a known opposite that defines what the prompt is NOT.

Architecture

• Stack: Python + NetworkX + numpy + SQLite + MCP SDK
• Graph: 1101 nodes, 1629 edges (10 branches × 100 constructs + 90 nexi + 1 central gem)
• Pipeline: 8 stages (Intent Parser → Coordinate Resolver → Position Computer → Construct Resolver → Tension Analyzer → Nexus/Gem Analyzer → Spoke Analyzer → Construction Bridge)
• Deployment: Single process, stdio transport, no daemon, no external dependencies

Documentation

• docs/DESIGN.md — Full design specification
• docs/CONSTRUCT.md — The Construct specification (what planes, points, spectrums, nexi, gems, spokes ARE)
• docs/CONSTRUCT-INTEGRATION.md — How Construct elements map to engine components
• docs/adr/ — 12 Architecture Decision Records
• docs/specs/ — 12 implementation specifications

Development

pip install -e ".[dev]"
pytest tests/ -v

Contributing

See CONTRIBUTING.md for development setup and guidelines.

Security

See SECURITY.md for vulnerability reporting instructions.

License

MIT