Policy Rules Reference

Introduction

The Axis Descriptor Lab includes a server-side relabelling endpoint, POST /api/relabel, used by the Auto (policy) toggle in the UI.

That endpoint tracks the current axis policy shipped in pipeworks_mud_server for the bundled world:

• data/worlds/pipeworks_web/policies/axes.yaml

• data/worlds/pipeworks_web/policies/thresholds.yaml

The mud server remains the runtime authority. Axis Lab keeps a checked-in lab-side copy of the current ordering and thresholds in app/relabel_policy.py so the UI can inspect and relabel deterministically without expanding the older local-mirror model into a second source of truth.

Mechanism

Matching uses inclusive score ranges derived from the mud-server thresholds.yaml files.

For each known axis:

1. Ranges are checked in declared order.

2. A label matches when min_score <= score <= max_score.

3. Unknown axes are left unchanged.

4. If a score falls outside every configured range, the existing label is preserved because the lab schema requires a non-empty string label.

Canonical Axis Order

The standalone slider UI uses the same full-axis order as the mud-server axes.yaml file:

1. physique

2. wealth

3. health

4. demeanor

5. age

6. facial_signal

7. legitimacy

8. visibility

9. moral_load

10. dependency

11. risk_exposure

When the chat page is connected to a mud server, the selected world’s active_axes order is shown first, and any remaining axes fall back to the canonical order above.

Policy Table

Physique

Score Range	Label
0.00 – 0.16	frail
0.17 – 0.32	hunched
0.33 – 0.48	skinny
0.49 – 0.64	wiry
0.65 – 0.80	broad
0.81 – 1.00	stocky

Wealth

Score Range	Label
0.00 – 0.19	poor
0.20 – 0.39	modest
0.40 – 0.59	well-kept
0.60 – 0.79	wealthy
0.80 – 1.00	decadent

Health

Score Range	Label
0.00 – 0.19	sickly
0.20 – 0.39	limping
0.40 – 0.59	weary
0.60 – 0.79	scarred
0.80 – 1.00	hale

Demeanor

Score Range	Label
0.00 – 0.19	timid
0.20 – 0.39	suspicious
0.40 – 0.59	resentful
0.60 – 0.79	alert
0.80 – 1.00	proud

Age

Score Range	Label
0.00 – 0.24	young
0.25 – 0.49	middle-aged
0.50 – 0.74	old
0.75 – 1.00	ancient

Facial Signal

Score Range	Label
0.00 – 0.14	understated
0.15 – 0.29	pronounced
0.30 – 0.44	exaggerated
0.45 – 0.59	asymmetrical
0.60 – 0.74	weathered
0.75 – 0.89	soft-featured
0.90 – 1.00	sharp-featured

Legitimacy

Score Range	Label
0.00 – 0.24	sanctioned
0.25 – 0.49	tolerated
0.50 – 0.74	questioned
0.75 – 1.00	illicit

Visibility

Score Range	Label
0.00 – 0.24	hidden
0.25 – 0.49	discrete
0.50 – 0.74	routine
0.75 – 1.00	conspicuous

Moral Load

Score Range	Label
0.00 – 0.24	neutral
0.25 – 0.49	burdened
0.50 – 0.74	conflicted
0.75 – 1.00	corrosive

Dependency

Score Range	Label
0.00 – 0.24	optional
0.25 – 0.49	useful
0.50 – 0.74	necessary
0.75 – 1.00	unavoidable

Risk Exposure

Score Range	Label
0.00 – 0.24	benign
0.25 – 0.49	straining
0.50 – 0.74	hazardous
0.75 – 1.00	eroding

Summary

Axis	Labels	Order Source
physique	6	axes.yaml
wealth	5	axes.yaml
health	5	axes.yaml
demeanor	5	axes.yaml
age	4	axes.yaml
facial_signal	7	axes.yaml
legitimacy	4	axes.yaml
visibility	4	axes.yaml
moral_load	4	axes.yaml
dependency	4	axes.yaml
risk_exposure	4	axes.yaml

Total: 11 axes, 52 configured labels.

Implementation Details

Source location

app/relabel_policy.py

Endpoint

POST /api/relabel

Data structures

AXIS_ORDER, AXIS_LABEL_ORDER, and RELABEL_POLICY: dict[str, list[tuple[float, float, str]]]

Matching algorithm

Inclusive range scan; first tuple satisfying min_score <= score <= max_score wins

Unknown axes

Passed through unchanged

Unmatched scores

Existing label preserved, because the lab payload schema requires a non-empty string label

Return value

New AxisPayload with relabelled axes and unchanged policy_hash, seed, and world_id