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personal-agent-skills

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  • License — License: MIT
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SUMMARY

A collection of distilled personal agent skills

README.md

personal-agent-skills

Tests
License
Python
Dependencies
Coverage

Sovereign Personal Agent Master Orchestrator for the OpenClaw / GenPark ecosystem. Built to liberate users from prompt fatigue, notification anxiety, and manual calendar juggling through zero-dependency mathematical modeling, circadian rhythm alignment, and ambient intent fusion.

flowchart TD
    subgraph AmbientInputs [Ambient Multi-Modal Sensing]
        A1[HRV & Physiological Readiness DFA-alpha1]
        A2[Screen Active Context & Typing Rhythm]
        A3[Calendar Proximity & Meeting Deadlines]
        A4[Inbound Notifications & Urgency Stream]
    end

    subgraph PersonalAgentKernel [Personal Agent Sovereign Kernel]
        K1[Circadian Energy Curve Modeler]
        K2[Ambient Focus State & Flow Classifier]
        K3[Proactive Intervention Utility Arbiter]
    end

    subgraph AutonomousOutcomes [Proactive Interventions]
        O1[Optimal Cognitive Workload Scheduling]
        O2[Silent Do-Not-Disturb Flow Protection]
        O3[Contextual Pre-Meeting Briefing]
        O4[Zero-Interruption Notification Drawer]
    end

    AmbientInputs --> PersonalAgentKernel
    PersonalAgentKernel --> AutonomousOutcomes

Distinctive Personal Agent Pillars

  1. Circadian Energy Awareness: Matches heavy cognitive tasks to physiological peak focus windows ($E(h) = R \cdot \exp(-((h - \mu)/\sigma)^2)$) rather than naive calendar packing.
  2. Ambient Zero-Prompt Ingress: Passively deduces user flow state from typing cadence, screen activity, and meeting proximity without demanding manual prompts.
  3. Utility-Gated Interruption Policy: Mathematically computes net interruption utility ($U = ext{Importance} - c \cdot ext{Focus}$), preventing distraction unless urgent.
  4. Local-First & Sovereign: 100% pure Python standard library. Zero third-party trackers, zero external telemetry leaks.

Curated Personal Agent Skills in the Ecosystem

Skill Repository Core Personal Capability
genpark-personal-agent-dynamic-hrv-dfa-alpha1-intensity-fractal-skill Real-time autonomic nervous system fatigue and DFA $\alpha_1$ aerobic-anaerobic threshold detection.
genpark-screen-zero-ambient-intent-scorer-skill Zero-click glance surface intent recognition on lockscreens and ambient displays.
genpark-screen-context Native desktop/mobile screen context OCR, UI element bounding, and active window state.
openclaw-genpark-memory-vault Episodic personal memory vault using ACT-R spreading activation decay.
openclaw-genpark-inbox-liquidator Automated personal inbox triage via Eisenhower matrix and auto-drafting.
genpark-meeting-to-tickets Converts spoken personal notes and meetings into structured Linear/Jira tasks.
genpark-student-space Spaced-repetition lifelong learning optimizer powered by SuperMemo SM-2.
genpark-phone-agent Personal inbound call screening, IVR navigation, and automated appointment setting.
openclaw-genpark-receipt-ledger Personal tax deduction tracking, receipt ledgering, and multi-currency expense reconciliation.
genpark-a2a-dating Sovereign Agent-to-Agent preference alignment using the Gale-Shapley stable matching algorithm.

Quickstart

from client import PersonalAgentOrchestrator

orchestrator = PersonalAgentOrchestrator()
tasks = [{"id": "t1", "title": "System Architecture Deep-Dive", "cognitive_load": 0.95}]
res = orchestrator.schedule_circadian_focus_blocks(tasks, circadian_peak_hour=10.5, current_hrv_readiness=0.90)

print("Scheduled Slot:", res["schedule"][0]["scheduled_slot"])
print("Average Cognitive Fit:", res["average_cognitive_fit"])

FastMCP Integration

python -m personal-agent-skills.mcp_server

License

MIT

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