Language Track·8 min read

The 10 N'Ko Sigils

A visual guide to cc-inscription's claim types and how each sigil detects patterns in motion trajectories.

ߛ ߜ ߕ ߙ ߡ ߚ ߞ ߣ ߠ ߥ

When motion flows through Comp-Core's pipeline, it eventually reaches the inscription layer. Here, continuous trajectories become discrete claims—typed statements about what the motion is doing, justified by evidence from the data.

Each claim type has a sigil: a N'Ko character that serves as both identifier and symbol. The sigils aren't arbitrary—they're drawn from a script designed to express meaning that doesn't map cleanly to other writing systems.

Structure of an inscription

[sigil] ⟦time-range⟧ : [evidence] ; [place] ; c=[confidence]

The 10 claim types

Stabilization

#01

Dispersion decreased

The trajectory is contracting. Variance across dimensions is dropping. The system is settling into a tighter state.

Examples

→Coming to rest
→Focusing attention
→Completing a gesture

Detection logic

σ(t) < σ(t-Δ) sustained for threshold duration

Dispersion

#02

Spread increased

The opposite of stabilization. The trajectory is expanding, exploring more state space. Variance is rising.

Examples

→Starting movement
→Searching
→Agitation

Detection logic

σ(t) > σ(t-Δ) sustained for threshold duration

Transition

#03

Change point

A boundary has been crossed. The trajectory has moved from one basin of attraction to another.

Examples

→Changing activity
→Switching context
→Phase boundary

Detection logic

basin(t) ≠ basin(t-1) with confidence above threshold

Return

#04

Re-entry to basin

The trajectory has returned to a previously visited basin. This is memory—the system recognizes where it's been.

Examples

→Coming home
→Resuming task
→Cyclical behavior

Detection logic

basin(t) ∈ history(basins) AND visit_count > 1

Dwell

#05

Sustained stay

The trajectory is remaining in the current basin longer than expected. Dwelling indicates commitment.

Examples

→Focused work
→Rest
→Waiting

Detection logic

time_in_basin > expected_duration(basin)

Oscillation

#06

Rapid alternation

The trajectory is bouncing between states. Not settling, not exploring—cycling.

Examples

→Indecision
→Pacing
→Rhythmic movement

Detection logic

transition_frequency > threshold AND basin_set.size ≤ 3

Recovery

#07

Return latency

After a perturbation, how quickly does the system return to baseline? Recovery measures resilience.

Examples

→Regaining balance
→Calming down
→Restoring focus

Detection logic

time_to_return(baseline) after perturbation event

Novelty

#08

New basin

A basin has been encountered that doesn't match any in history. This is genuine discovery.

Examples

→New place
→New movement
→Learning

Detection logic

basin(t) ∉ history(basins) with confidence above threshold

Place-Shift

#09

Location change

The trajectory has moved in physical or semantic place space. Context has changed.

Examples

→Moving rooms
→Changing environments
→Contextual shift

Detection logic

place(t) ≠ place(t-Δ) where place is higher-level than basin

Echo

#10

Pattern recurrence

A temporal pattern has repeated. Not just returning to a basin, but replicating a sequence.

Examples

→Routine
→Habit
→Rhythmic pattern

Detection logic

sequence_similarity(recent, history) > threshold

How detectors work

Each sigil has a dedicated detector in cc-inscription. Detectors receive a MotionWindow (the output of the motion pipeline) plus context: current place, slice ID, and access to basin history.

A detector outputs a typed intermediate representation (IR) if it fires, or nothing if it doesn't. The IR includes:

•Claim type — which sigil
•Time interval — when it occurred
•Evidence references — what triggered it
•Confidence — how certain [0, 1]
•Place — where (basin, location, context)

Provenance chain

Every inscription is traceable. From the final N'Ko surface form, you can walk back through:

Surface form←Typed IR←Evidence←MotionWindow←Raw sensors

This chain is what makes inscriptions "justified" rather than just "labeled." You can audit why the system made a claim, not just what claim it made.

Why 10 sigils?

The current set covers the fundamental behaviors we've identified in trajectory dynamics:

State change

ߛ ߜ ߕ — stabilization, dispersion, transition

Memory

ߙ ߡ ߣ — return, dwell, novelty

Dynamics

ߚ ߞ — oscillation, recovery

Context

ߠ ߥ — place-shift, echo

The set is designed to be complete enough to describe most trajectory behaviors while remaining small enough that each sigil has clear meaning. New sigils can be added, but the bar is high—they must detect something genuinely distinct.

"Each sigil is a hypothesis about what patterns matter in motion. The set evolves as we learn what the body is actually saying."

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