MCPInstall

continue-claude-work

Recover actionable context from local .claude session artifacts and continue interrupted work without running claude --resume. This skill should be used when the user provides a Claude session ID, asks to continue prior work from local history, or wants to inspect .claude files before resuming implementation.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/daymade/claude-code-skills --skill continue-claude-work
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads continue-claude-work automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Continue Claude Work

Overview

Recover actionable context from a prior Claude Code session and continue execution in the current conversation. Use local session files as the source of truth, then continue with concrete edits and checks — not just summarizing.

Why this exists instead of claude --resume: claude --resume replays the full session transcript into the context window. For long sessions this wastes tokens on resolved issues and stale state. This skill selectively reconstructs only actionable context — the latest compact summary, pending work, known errors, and current workspace state — giving a fresh start with prior knowledge.

File Structure Reference

For directory layout, JSONL schemas, and compaction block format, see references/file_structure.md.

Workflow

Step 1: Extract Context (single script call)

Run the bundled extraction script. It handles session discovery, compact-boundary parsing, noise filtering, and workspace state in one call:

# Latest session for current project
python3 scripts/extract_resume_context.py

# Specific session by ID
python3 scripts/extract_resume_context.py --session <SESSION_ID>

# Search by topic
python3 scripts/extract_resume_context.py --query "auth feature"

# List recent sessions
python3 scripts/extract_resume_context.py --list

The script outputs a structured Markdown briefing containing:

  • Session metadata from sessions-index.json
  • Compact summary — Claude's own distilled summary from the last compaction boundary (highest-signal context)
  • Last user requests — the most recent explicit asks
  • Last assistant responses — what was claimed done
  • Errors encountered — tool failures and error outputs
  • Unresolved tool calls — indicates interrupted session
  • Subagent workflow state — which subagents completed, which were interrupted, their last outputs
  • Session end reason — clean exit, interrupted (ctrl-c), error cascade, or abandoned
  • Files touched — files created/edited/read during the session
  • MEMORY.md — persistent cross-session notes
  • Git state — current status, branch, recent log

The script automatically skips the currently active session (modified < 60s ago) to avoid self-extraction.

Step 2: Branch by Session End Reason

The briefing includes a Session end reason. Use it to choose the right continuation strategy:

End ReasonStrategy
Clean exitSession completed normally. Read the last user request that was addressed. Continue from pending work if any.
InterruptedTool calls were dispatched but never got results (likely ctrl-c or timeout). Retry the interrupted tool calls or assess whether they are still needed.
Error cascadeMultiple API errors caused the session to fail. Do not retry blindly — diagnose the root cause first.
AbandonedUser sent a message but got no response. Treat the last user message as the current request.

If the briefing has a Subagent Workflow section with interrupted subagents, check what each was doing and whether to retry or skip.

Step 3: Reconcile and Continue

Before making changes:

  1. Confirm the current directory matches the session's project.
  2. If the git branch has changed from the session's branch, note this and decide whether to switch.
  3. Inspect files related to pending work — verify old claims still hold.
  4. Do not assume old claims are valid without checking.

Then:

  • Implement the next concrete step aligned with the latest user request.
  • Run deterministic verification (tests, type-checks, build).
  • If blocked, state the exact blocker and propose one next action.

Step 4: Report

Respond concisely:

  • Context recovered: which session, key findings from the briefing
  • Work executed: files changed, commands run, test results
  • Remaining: pending tasks, if any

How the Script Works

Compact-Boundary-Aware Extraction

The script finds the last compact boundary in the session JSONL and extracts its summary. This is the single highest-signal piece of context in any long session -- Claude's own distilled understanding of the entire conversation up to that point. For details on compaction format and JSONL schemas, see references/file_structure.md.

Size-Adaptive Strategy

Session sizeStrategy
Has compactionsRead last compact summary + all post-compact messages
< 500 KB, no compactionsRead last 60% of messages
500 KB - 5 MBRead last 30% of messages
> 5 MBRead last 15% of messages

Subagent Context Extraction

When a session has subagent directories (<session-id>/subagents/), the script parses each subagent's JSONL to extract agent type, completion status, and last text output. This enables recovery of multi-agent workflows -- e.g., if a 32-subagent evaluation pipeline was interrupted, the briefing shows which agents completed and which need retry.

Session End Reason Detection

The script classifies how the session ended:

  • completed -- assistant had the last word (clean exit)
  • interrupted -- unresolved tool calls (ctrl-c or timeout)
  • error_cascade -- 3+ API errors
  • abandoned -- user sent a message with no response

Noise Filtering

These message types are skipped (37-53% of lines in real sessions):

  • progress, queue-operation, file-history-snapshot -- operational noise
  • api_error, turn_duration, stop_hook_summary -- system subtypes
  • <task-notification>, <system-reminder> -- filtered from user text extraction

Guardrails

  • Do not run claude --resume or claude --continue — this skill provides context recovery within the current session.
  • Do not treat compact summaries as complete truth — they are lossy. Always verify claims against current workspace.
  • Do not overwrite unrelated working-tree changes.
  • Do not load the full session file into context — always use the script.

Limitations

  • Cannot recover sessions whose .jsonl files have been deleted from ~/.claude/projects/.
  • Cannot access sessions from other machines (files are local only).
  • Edit tool operations show deltas, not full file content — use claude-code-history-files-finder for full file recovery.
  • Compact summaries are lossy — early conversation details may be missing.
  • sessions-index.json can be stale (entries pointing to deleted files). The script falls back to filesystem-based discovery.

Example Trigger Phrases

  • "continue work from session abc123-..."
  • "don't resume, just read the .claude files and continue"
  • "check what I was working on in the last session and keep going"
  • "search my sessions for the PR review work"

FAQ

What does the continue-claude-work skill do?

Recover actionable context from local .claude session artifacts and continue interrupted work without running claude --resume. This skill should be used when the user provides a Claude session ID, asks to continue prior work from local history, or wants to inspect .claude files before resuming implementation.

How do I install continue-claude-work?

Run npx skills add https://github.com/daymade/claude-code-skills --skill continue-claude-work in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/continue-claude-work/ (personal) or .claude/skills/continue-claude-work/ (project).

Which AI agents can use continue-claude-work?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is continue-claude-work safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains continue-claude-work?

It is published by daymade in daymade/claude-code-skills. It has 631 recorded installs.

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