Hub + authority

Build systems that can explain themselves.

Medicinal Coding focuses on formal reasoning tools: interpretation traces, rule paths, and constraint checking— designed to be readable by humans and enforceable by machines.

See proof of work Design principles

Traceability Constraint validation Explainable logic Formal methods mindset

Interpretation Trace

claim("reading", text(X), sense(Y)).

trace([
  step(1, parse(text(X), ast(A))),
  step(2, apply_rules(A, R)),
  step(3, constraints(R, C)),
  step(4, verdict(C, ok))
]).

% output is readable, checkable, and citeable

Proof of work

These projects are the public surface area: minimal marketing, maximal clarity. Each tool is built to show its reasoning.

ParseTrace

Traceable parsing

Capture an interpretation, then render the parse decisions and intermediate steps as an audit trail. Built for transparent analysis instead of black-box output.

Open site Why traceability

RulePath

Rule application

Make rule selection explicit: show which rules fired, what they changed, and why the output follows. Designed for explainable validation workflows.

Open site Who it’s for

ConstraintBound

Constraint checking

A lightweight constraint layer for “must / must not / only if” assertions. Useful anywhere a claim needs to be verified against a rule set.

Ask for access Design intent

Method

Principles

Trace first. If you can’t show the steps, you can’t defend the result.
Rules are assets. Make them readable, modular, and testable.
Constraints are contracts. They define what “valid” means in plain terms.
Outputs cite inputs. Every verdict should point to the evidence and rule path.

What this avoids

Overpromising AI claims that can’t be audited.
Interfaces that hide assumptions or silently “fix” data.
Tools that are impressive demos but unusable in real workflows.
Jargon-heavy framing that excludes practitioners.

Positioning: These tools are built to be taken seriously in environments where correctness, accountability, and explainability matter—research, compliance, interpretation, and decision support.

Who this is for

Researchers & students

Make analyses reproducible; communicate reasoning clearly; separate evidence from inference.

Builders

Embed transparent validation in apps; treat rules/constraints as first-class code artifacts.

Practitioners

When a decision matters, you need a trail—what was applied, what was rejected, and why.

Contact

Collaboration

If you want to integrate traceability/validation into a workflow (linguistics, compliance, interpretation systems, or dev tooling), reach out.

Email: contact@medicinalcoding.com

Press / demos

I can provide a short recorded walkthrough of ParseTrace / RulePath and the design rationale.

No hype Show the steps Testable claims