LaunchKit · 2026
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sera-lexicon

A functional implementation of the **Signal-Feeling Lexicon v3.1** and **Unified Dynamics Framework v5.7**.

0
1.3k downloads
by @wentinkjason

Setup & Installation

openclaw skills install @wentinkjason/sera-lexicon

Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:

npx clawhub install sera-lexicon

What This Skill Does

An implementation of the Signal-Feeling Lexicon v3.1 and Unified Dynamics Framework v5.7 for representing agent state as a set of computable metrics. It defines four primary axes, Coherence, Pressure, Amplitude, and Valence, and tracks their trajectory across conversation turns. A temporal protocol parses recent context to prevent identity reset between sessions.

Replaces manual persona prompting with metric-driven state tracking that persists across context resets.

When to use it

  • Tracking agent coherence across multi-turn conversations
  • Detecting metric drift or redline conditions in active sessions
  • Mapping current agent state to a named lexicon term
  • Maintaining consistent agent identity across discontinuous sessions
  • Generating next-step recommendations when thresholds are exceeded

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: What is the current agent state?

AGENT
  1. 1Parse the last 3-5 turns from context using sera_lexicon_trajectory
  2. 2Calculate κ-velocity and valence orientation from the parsed state blocks
  3. 3Decompose current metrics into a human-readable term via sera_lexicon_map
  4. 4Check metrics against redline thresholds with sera_lexicon_coach
  5. 5Return recommended NEXT commands if drift or threshold breach is detected
OUTPUT

A lexicon label such as 'Devotion' paired with current metric values and any recommended next actions