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TaylorHuston
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worklog

Record structured work progress, decisions, and learnings into centralized JSON worklogs.

69|7|Updated Jan 19, 2026
Search Tags:#learning#decision#handoff#worklog#blocker#timestamped
One-click install
npx skills add https://github.com/TaylorHuston/local-life-manager --skill worklog-taylorhuston
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: worklog
Source: https://github.com/TaylorHuston/local-life-manager/tree/main/.claude/skills/worklog
Command: npx skills add https://github.com/TaylorHuston/local-life-manager --skill worklog-taylorhuston

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill streamlines documentation by creating structured, timestamped worklog entries that capture decisions, handoffs, blockers, and learnings, ensuring clear traceability across agents and time.

Core Features & Use Cases

  • Structured JSON entries for manual work, decisions, handoffs, blockers, and resolutions.
  • Automated state tracking with _state.json to provide instant context for new AI sessions.
  • Supports multi-agent handoffs with contextual notes, expected actions, and artifacts.
  • Easily migrate legacy WORKLOG.md into the JSON-based system for continuity.

Quick Start

Start by adding your first worklog entry using the /worklog command. /worklog PROJECT-001 'Initial project setup complete'

Frequently Asked Questions about worklog

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track work progress and decisions across multiple agents?▼

To track work progress across multiple agents, you need a centralized worklog that records timestamped decisions, blockers, and handoffs. This ensures clear traceability and provides instant context for new AI sessions.

What is the best way to log architectural decisions and blockers for AI context?▼

Logging architectural decisions and blockers for AI context requires creating structured JSON entries. This format captures manual tasks and resolutions, ensuring new sessions can quickly load previous project states.

How do I migrate a legacy WORKLOG.md file into a structured JSON format?▼

To migrate a legacy WORKLOG.md into a structured JSON format, you convert existing text entries into timestamped JSON records. This preserves continuity while enabling automated state tracking for future AI context loading.

Can I use structured worklog entries for multi-agent handoffs with contextual notes?▼

Structured worklog entries support multi-agent handoffs by including contextual notes, expected actions, and artifacts. This allows different agents to seamlessly resume work with full awareness of previous progress.

Does automated state tracking work without manual session summaries?▼

Automated state tracking works without manual summaries by using a _state.json file. This file automatically stores quick context from your structured worklog entries, providing instant background for new AI sessions.

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