continuity-ledger

parcadei/continuous-claude-v3 · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill continuity-ledger
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summary

Note: This skill is now an alias for /create_handoff. Both output the same YAML format.

skill.md

Continuity Ledger

Note: This skill is now an alias for /create_handoff. Both output the same YAML format.

Create a YAML handoff document for state preservation across /clear. This is the same as /create_handoff.

Process

1. Filepath & Metadata

First, determine the session name from existing handoffs:

ls -td thoughts/shared/handoffs/*/ 2>/dev/null | head -1 | xargs basename

This returns the most recently modified handoff folder name (e.g., open-source-release). Use this as the handoff folder name.

If no handoffs exist, use general as the folder name.

Create your file under: thoughts/shared/handoffs/{session-name}/YYYY-MM-DD_HH-MM_description.yaml, where:

  • {session-name} is from existing handoffs (e.g., open-source-release) or general if none exist
  • YYYY-MM-DD is today's date
  • HH-MM is the current time in 24-hour format (no seconds needed)
  • description is a brief kebab-case description

Examples:

  • thoughts/shared/handoffs/open-source-release/2026-01-08_16-30_memory-system-fix.yaml
  • thoughts/shared/handoffs/general/2026-01-08_16-30_bug-investigation.yaml

2. Write YAML handoff (~400 tokens)

CRITICAL: Use EXACTLY this YAML format. Do NOT deviate or use alternative field names.

The goal: and now: fields are shown in the statusline - they MUST be named exactly this.

---
session: {session-name from ledger}
date: YYYY-MM-DD
status: complete|partial|blocked
outcome: SUCCEEDED|PARTIAL_PLUS|PARTIAL_MINUS|FAILED
---

goal: {What this session accomplished - shown in statusline}
now: {What next session should do first - shown in statusline}
test: {Command to verify this work, e.g., pytest tests/test_foo.py}

done_this_session:
  - task: {First completed task}
    files: [{file1.py}, {file2.py}]
  - task: {Second completed task}
    files: [{file3.py}]

blockers: [{any blocking issues}]

questions: [{unresolved questions for next session}]

decisions:
  - {decision_name}: {rationale}

findings:
  - {key_finding}: {details}

worked: [{approaches that worked}]
failed: [{approaches that failed and why}]

next:
  - {First next step}
  - {Second next step}

files:
  created: [{new files}]
  modified: [{changed files}]

Field guide:

  • goal: + now: - REQUIRED, shown in statusline
  • done_this_session: - What was accomplished with file references
  • decisions: - Important choices and rationale
  • findings: - Key learnings
  • worked: / failed: - What to repeat vs avoid
  • next: - Action items for next session

DO NOT use alternative field names like session_goal, objective, focus, current, etc. The statusline parser looks for EXACTLY goal: and now: - nothing else works.

3. Mark Session Outcome (REQUIRED)

IMPORTANT: Before responding to the user, you MUST ask about the session outcome.

Use the AskUserQuestion tool with these exact options:

Question: "How did this session go?"
Options:
  - SUCCEEDED: Task completed successfully
  - PARTIAL_PLUS: Mostly done, minor issues remain
  - PARTIAL_MINUS: Some progress, major issues remain
  - FAILED: Task abandoned or blocked

After the user responds, mark the outcome:

# Mark the most recent handoff (works with PostgreSQL or SQLite)
PROJECT_ROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "${CLAUDE_PROJECT_DIR:-.}")
cd "$PROJECT_ROOT/opc" && uv run python scripts/core/artifact_mark.py --latest --outcome <USER_CHOICE>

4. Confirm completion

After marking the outcome, respond to the user:

Handoff created! Outcome marked as [OUTCOME].

Resume in a new session with:
/resume_handoff path/to/handoff.yaml

When to Use

  • Before running /clear
  • Context usage approaching 70%+
  • Multi-day implementations
  • Complex refactors you pick up/put down
  • Any session expected to hit 85%+ context

When NOT to Use

  • Quick tasks (< 30 min)
  • Simple bug fixes
  • Single-file changes

Why Clear Instead of Compact?

Each compaction is lossy compression—after several compactions, you're working with degraded context. Clearing + loading the handoff gives you fresh context with full signal.

how to use continuity-ledger

How to use continuity-ledger on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add continuity-ledger
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill continuity-ledger

The skills CLI fetches continuity-ledger from GitHub repository parcadei/continuous-claude-v3 and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/continuity-ledger

Reload or restart Cursor to activate continuity-ledger. Access the skill through slash commands (e.g., /continuity-ledger) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.631 reviews
  • Valentina White· Dec 24, 2024

    Keeps context tight: continuity-ledger is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ganesh Mohane· Dec 4, 2024

    We added continuity-ledger from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Lucas Khanna· Nov 15, 2024

    continuity-ledger is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Lucas Desai· Oct 6, 2024

    continuity-ledger fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Rahul Santra· Sep 25, 2024

    continuity-ledger fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Hiroshi Desai· Sep 13, 2024

    continuity-ledger has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Li Harris· Sep 1, 2024

    Useful defaults in continuity-ledger — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Layla Chen· Aug 28, 2024

    continuity-ledger fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chinedu Malhotra· Aug 20, 2024

    continuity-ledger has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Pratham Ware· Aug 16, 2024

    continuity-ledger is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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