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, 1459 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 specificationdocs/CONSTRUCT.md— The Construct specification (what planes, points, spectrums, nexi, gems, spokes ARE)docs/CONSTRUCT-INTEGRATION.md— How Construct elements map to engine componentsdocs/adr/— 12 Architecture Decision Recordsdocs/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