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tegwick 574bb11db6 feat(example): add supply-chain-vsm composition demo (S3.5)

Demonstrates infospace composition: the Wealth of Nations infospace is
used as a discipline, applying Smith's economic framework as a lens to
analyse modern supply chain management concepts.

New example: examples/supply-chain-vsm/
- infospace.yaml binding WoN as discipline (../infospace-with-history)
- 3 source documents: coordination mechanisms, capital & inventory,
  market structure (~400 words each, original content)
- supply-chain-entity-schema-v1.0.md with WoN Concept required section
- won-mapping-schema-v1.0.md with Conceptual Continuity rating
- artifacts/won-reference/core-entities.md — 12 curated WoN entities
  for injection as discipline context
- 8 hand-crafted entity files demonstrating LLM output format
- 3 mapping files with full rationale and VSM inheritance chains
- Viable: YES (5/5 thresholds)

Key mappings demonstrated:
  Demand Signal          → Effectual Demand        (Strong, S2)
  Vendor-Managed Inventory → Division of Labour    (Strong, S1/S2)
  Just-in-Time Inventory → Circulating Capital     (Strong, S1/S3)
  Bullwhip Effect        → Natural Price           (Moderate, S2)
  Platform Intermediary  → Merchant Capital        (Strong, S2/S4)
  Monopsony Power        → Combination of Masters  (Strong, S3*)

Platform fix: entity_parser.py now recognises ## Supply Chain Domain
as a domain alias for ## Economic Domain, enabling composed infospaces
to use their own domain section name.

Tutorial §13 rewritten with real commands, real output, and the full
mapping table from the demo.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-02-23 00:08:51 +01:00

artifacts

fix(example): standardise domain enum and source chapter format in schema/rules

2026-02-19 13:02:05 +01:00

output

chore(example): final metrics snapshot — all 35 chapters processed

2026-02-19 22:54:54 +01:00

schemas

fix(example): standardise domain enum and source chapter format in schema/rules

2026-02-19 13:02:05 +01:00

templates

fix(pipeline): retry on 0-entity response, save raw debug, improve template

2026-02-19 14:26:28 +01:00

infospace.yaml

fix(infospace): exclude raw LLM output from entity parsing; lower coverage threshold

2026-02-20 09:28:20 +01:00

INFRA-TASKS.md

docs: metrics methodology, collection-level tasks, and infospace tooling roadmap

2026-02-18 23:53:21 +01:00

LAYERED-DEVELOPMENT.md

docs(example): add layered development concept and extend tutorial

2026-02-20 10:43:32 +01:00

METRICS-METHODOLOGY.md

docs(metrics): clarify C2 coverage — domain×chapter matrix, not domain×VSM

2026-02-20 00:08:46 +01:00

process_chapters.py

feat(example): migrate to infospace config with tooling integration (S3.1)

2026-02-19 02:29:53 +01:00

README.md

feat(llm): add Gemini adapter and process book-1-chapter-05

2026-02-11 22:54:37 +01:00

TUTORIAL.md

feat(example): add supply-chain-vsm composition demo (S3.5)

2026-02-23 00:08:51 +01:00

README.md

This example provides a tutorial and reference experiment for how to set up a viable infospace with history using markitect.

The task is to capture the knowledge from Adam Smith's The Wealth of Nations available digitally in the public domain as a transcript of the original text and transform and extend it to a collection of concepts and entities from a systems theoretical point of view based on Stafford Beer's Viable System Model that is consistent and complete.

The tutorial should explain how to use the concept of schemas to provide a scaffolding for how to structure the necessary information entities and define a set of prompts and instructions using the prompt dependency resolution infrastructure to incrementally inject chapters of the book.

The information space should utilize the option of keeping changes as git history. And define metrics for completeness and consistency.

While running the experiment no changes must be made to the markitect infrastructure.

If demand for optimization or fixing errors occurs, a list of corresponding tasks should be generated. It will be used to optimize the markitect infrastructure to then rerun the experiment to optimize tooling and infospace over time and again.

--worsch, 10th Feb. 2026