py-dianoia 0.1.0

Open-source expert reasoning framework distillation tool

Dianoia AI 格物致知

Open-source expert reasoning framework distillation tool

English | 中文

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What is Dianoia?

Dianoia (格物致知) distills expert reasoning patterns from public artifacts — documents, code reviews, design docs — into profile.yaml and SKILL.md formats that any AI agent can consume.

Unlike knowledge extraction, Dianoia captures how experts think: how they define problems, judge quality, prioritize trade-offs, and decide when "good enough" is acceptable.

Inspired by The Relic Condition research on reasoning architecture extraction.

Install

pip install py-dianoia

Requires Python 3.11+

Quick Start

# 1. Initialize a project
dianoia init my-expert

# 2. Add corpus files to my-expert/corpus/
cp ~/expert-docs/*.md my-expert/corpus/

# 3. Extract reasoning patterns
dianoia extract my-expert

# 4. Build output files (profile.yaml + SKILL.md)
dianoia build my-expert

# 5. Validate outputs
dianoia validate my-expert

Architecture

Corpus Files → ExtractionPipeline (8 layers) → IR → ProfileMapper → profile.yaml
                                                     → SkillRenderer  → SKILL.md

8-Layer Extraction Method

#	Layer	Extracts
1	Ontological	Problem boundaries, classification systems
2	Teleological	Goals, purposes, end-driven reasoning
3	Methodological	Procedures, systematic approaches
4	Axiological	Values, priorities, decision criteria
5	Epistemological	Knowledge sources, evidence standards
6	Conditional	Context-dependent decisions
7	Priority	Trade-off ordering (engineering-specific)
8	Pragmatic	"Good enough" thresholds, practical shortcuts

Stability Filtering

Features only survive if they appear in ≥2 independent texts AND ≥3 distinct contexts. This filters noise and ensures distilled patterns represent genuine expert consensus.

Output Formats

profile.yaml

Structured data for workflow engines (e.g., kitchen-ent):

version: "1.0"
sections:
  identity:
    - key: domain
      value: engineering
      confidence: 0.85
      sources: [doc1.md, doc2.md]

SKILL.md

Follows the Agent Skills open standard:

---
name: "my-expert"
description: "Expert reasoning distilled from ..."
---

# My Expert

## Extracted Reasoning Patterns
...

Language Overlay

Distill once in a language-agnostic base profile, then overlay language-specific customizations:

base-profile.yaml (language-agnostic skeleton)
  + overlay-python.yaml
  + overlay-rust.yaml
  + overlay-go.yaml

Documentation

• Distillation Principle
• Architecture
• CLI Reference
• Language Overlay
• Profile Deliverable
• SKILL Deliverable
• Contributing

Specifications

• IR Schema — JSON Schema for the Intermediate Representation
• Profile Spec — profile.yaml format specification
• SKILL Spec — SKILL.md format specification

Development

git clone https://github.com/bigmoon-dev/dianoia-ai.git
cd dianoia-ai
pip install -e ".[dev]"
pytest

License

Apache-2.0