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genpark-personal-agent-attention-residue-context-switch-skill

mcp
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  • License — License: MIT
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  • Active repo — Last push 0 days ago
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SUMMARY

Personal Agent Attention Residue Context Switch - Zero-dependency Leroy attention residue decay modeler, multi-application context fragmentation entropy calculator, and optimal task batching schedule optimizer.

README.md

genpark-personal-agent-attention-residue-context-switch-skill

Tests
License
Python
Dependencies
Coverage

GenPark Personal Agent Attention Residue Context Switch models Sophie Leroy's attention residue theory and Shannon application entropy to protect personal deep work.

flowchart TD
    A[Task Switch Log & Unfinished Task States] --> B[Leroy Attention Residue Decay Engine]
    B --> C[Cognitive Tax Minutes Lost Per Switch]
    D[Active Application Time Distribution] --> E[Shannon Fragmentation Entropy Calculator]
    F[Unstructured To-Do List] --> G[Optimal Context Batching Optimizer]
    C & E & G --> H[Recovered Deep Work Hours]

Features

  • Attention Residue Quantification: Calculates minutes of mental capacity lost to unfinished task transitions.
  • Application Entropy Scoring: Measures digital multitasking thrashing across active desktop windows.
  • Intelligent Context Batching: Groups related tasks to eliminate up to 75% of daily context switches.

Quickstart

from client import PersonalAgentAttentionResidueContextSwitch

residue = PersonalAgentAttentionResidueContextSwitch()
res = residue.optimize_task_batching_schedule([{"title": "Email 1", "category": "INBOX"}, {"title": "Email 2", "category": "INBOX"}])
print("Recovered Focus Minutes:", res["estimated_recovered_focus_minutes"])

FastMCP Integration

python -m genpark-personal-agent-attention-residue-context-switch-skill.mcp_server

License

MIT

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