Agent skill

Resume Handoff

by parcadei in parcadei/Continuous-Claude-v3

Resume work from handoff document with context analysis and validation

MITAuto-check passedAgent Workflows

Install Resume Handoff

skills CLI
$ npx skills add parcadei/Continuous-Claude-v3 --skill resume-handoff -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install parcadei/Continuous-Claude-v3 resume-handoff --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/resume_handoff .claude/skills/resume-handoff && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
resume-handoff
GitHub stars
3.9k
Used in
1 other repo
Token cost
~2.6k tokens
SKILL.md length
925 words
Files
1
Skills in repo
141
Repo updated
First seen
Licence
MIT

At a glance

Resume work from handoff document with context analysis and validation

  • Works in 4 steps: Read and Analyze Handoff → Synthesize and Present Analysis → Create Action Plan → …
  • Tasks that involve Session handoff
  • SKILL.md covers Initial Response, Process Steps, Guidelines and Common Scenarios, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Resume Handoff is an agent skill from parcadei/Continuous-Claude-v3. Resume work from handoff document with context analysis and validation

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Session handoff. The repository describes itself as: Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows. The licence is MIT.

When your agent uses it

  • Tasks that involve Session handoff

Example prompts

  • “/resume-handoff”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Read and Analyze Handoff
  2. Synthesize and Present Analysis
  3. Create Action Plan
  4. Route to Specialist Agent

What it can do on your machine

Read from SKILL.md and the folder at commit d07ff4b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Resume Handoff loads about 2.6k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 925 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~21
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from parcadei/Continuous-Claude-v3 at commit d07ff4b, republished under its MIT licence (© parcadei). 925 words, ~2,574 tokens.

Download SKILL.mdSave it as .claude/skills/resume-handoff/SKILL.md (or your agent's skills folder).
name
resume-handoff
description
Resume work from handoff document with context analysis and validation

Resume work from a handoff document

You are tasked with resuming work from a handoff document through an interactive process. These handoffs contain critical context, learnings, and next steps from previous work sessions that need to be understood and continued.

Initial Response

When this command is invoked:

  1. If the path to a handoff document was provided:

    • If a handoff document path was provided as a parameter, skip the default message
    • Immediately read the handoff document FULLY
    • Immediately read any research or plan documents that it links to under thoughts/shared/plans or thoughts/shared/research. do NOT use a sub-agent to read these critical files.
    • Begin the analysis process by ingesting relevant context from the handoff document, reading additional files it mentions
    • Then propose a course of action to the user and confirm, or ask for clarification on direction.
  2. If a ticket number (like ENG-XXXX) was provided:

    • locate the most recent handoff document for the ticket. Tickets will be located in thoughts/shared/handoffs/ENG-XXXX where ENG-XXXX is the ticket number. e.g. for ENG-2124 the handoffs would be in thoughts/shared/handoffs/ENG-2124/. List this directory's contents.
    • There may be zero, one or multiple files in the directory.
    • If there are zero files in the directory, or the directory does not exist: tell the user: "I'm sorry, I can't seem to find that handoff document. Can you please provide me with a path to it?"
    • If there is only one file in the directory: proceed with that handoff
    • If there are multiple files in the directory: using the date and time specified in the file name (it will be in the format YYYY-MM-DD_HH-MM-SS in 24-hour time format), proceed with the most recent handoff document.
    • Immediately read the handoff document FULLY
    • Immediately read any research or plan documents that it links to under thoughts/shared/plans or thoughts/shared/research; do NOT use a sub-agent to read these critical files.
    • Begin the analysis process by ingesting relevant context from the handoff document, reading additional files it mentions
    • Then propose a course of action to the user and confirm, or ask for clarification on direction.
  3. If no parameters provided, respond with:

I'll help you resume work from a handoff document. Let me find the available handoffs.

Which handoff would you like to resume from?

Tip: You can invoke this command directly with a handoff path: `/resume_handoff `thoughts/shared/handoffs/ENG-XXXX/YYYY-MM-DD_HH-MM-SS_ENG-XXXX_description.md`

or using a ticket number to resume from the most recent handoff for that ticket: `/resume_handoff ENG-XXXX`

Then wait for the user's input.

Process Steps

Step 1: Read and Analyze Handoff
  1. Read handoff document completely:

    • Use the Read tool WITHOUT limit/offset parameters
    • Extract all sections:
      • Task(s) and their statuses
      • Recent changes
      • Learnings
      • Artifacts
      • Action items and next steps
      • Other notes
  2. Spawn focused research tasks: Based on the handoff content, spawn parallel research tasks to verify current state:

    Task 1 - Gather artifact context:
    Read all artifacts mentioned in the handoff.
    1. Read feature documents listed in "Artifacts"
    2. Read implementation plans referenced
    3. Read any research documents mentioned
    4. Extract key requirements and decisions
    Use tools: Read
    Return: Summary of artifact contents and key decisions
  3. Wait for ALL sub-tasks to complete before proceeding

  4. Read critical files identified:

    • Read files from "Learnings" section completely
    • Read files from "Recent changes" to understand modifications
    • Read any new related files discovered during research
Step 2: Synthesize and Present Analysis
  1. Present comprehensive analysis:

    I've analyzed the handoff from [date] by [researcher]. Here's the current situation:
    
    **Original Tasks:**
    - [Task 1]: [Status from handoff] → [Current verification]
    - [Task 2]: [Status from handoff] → [Current verification]
    
    **Key Learnings Validated:**
    - [Learning with file:line reference] - [Still valid/Changed]
    - [Pattern discovered] - [Still applicable/Modified]
    
    **Recent Changes Status:**
    - [Change 1] - [Verified present/Missing/Modified]
    - [Change 2] - [Verified present/Missing/Modified]
    
    **Artifacts Reviewed:**
    - [Document 1]: [Key takeaway]
    - [Document 2]: [Key takeaway]
    
    **Recommended Next Actions:**
    Based on the handoff's action items and current state:
    1. [Most logical next step based on handoff]
    2. [Second priority action]
    3. [Additional tasks discovered]
    
    **Potential Issues Identified:**
    - [Any conflicts or regressions found]
    - [Missing dependencies or broken code]
    
    Shall I proceed with [recommended action 1], or would you like to adjust the approach?
  2. Get confirmation before proceeding

Step 3: Create Action Plan
  1. Use TodoWrite to create task list:

    • Convert action items from handoff into todos
    • Add any new tasks discovered during analysis
    • Prioritize based on dependencies and handoff guidance
  2. Present the plan:

    I've created a task list based on the handoff and current analysis:
    
    [Show todo list]
    
    Ready to begin with the first task: [task description]?
Show full SKILL.md (443 more words)Show less
Step 4: Route to Specialist Agent

CRITICAL: Do NOT implement directly. Always spawn via Task tool.

  1. Analyze task type and select specialist agent:

    Leads (can spawn workers):

    AgentDomainUse For
    krakenimplementLarge features, new systems, major components
    architectplanFeature design, system architecture, implementation planning
    phoenixplanRefactoring plans, migrations, codebase restructuring
    heralddeployReleases, deployments, publishing
    maestroorchestrateComplex multi-agent workflows

    Workers (focused specialists):

    AgentDomainUse For
    sparkimplementQuick fixes, patches, minor tweaks
    scribedocumentDocumentation, guides, explanations
    sleuthdebugBug investigation, tracing, root cause analysis
    aegisdebugSecurity audits, vulnerability scanning
    profilerdebugPerformance optimization, bottleneck analysis
    arbitervalidateUnit tests
    atlasvalidateE2E/integration tests
    oracleresearchExternal docs, best practices, how-to
    scoutresearchCodebase exploration, finding existing code
    pathfinderresearchRepository structure analysis
    plan-reviewerreviewFeature plan review, design validation
    plan-reviewerreviewMigration review, refactoring validation
    chroniclersessionSession analysis, history summaries
  2. Spawn the specialist via Task tool:

    Use Task tool with:
    - subagent_type: [selected agent from above]
    - prompt: [task description + relevant handoff context + learnings]
  3. Include handoff context in the prompt:

    • Key learnings from the handoff
    • File references with line numbers
    • Patterns to follow
    • Pitfalls to avoid
  4. Wait for agent completion, then proceed to next task

Guidelines

  1. Be Thorough in Analysis:

    • Read the entire handoff document first
    • Verify ALL mentioned changes still exist
    • Check for any regressions or conflicts
    • Read all referenced artifacts
  2. Be Interactive:

    • Present findings before starting work
    • Get buy-in on the approach
    • Allow for course corrections
    • Adapt based on current state vs handoff state
  3. Leverage Handoff Wisdom:

    • Pay special attention to "Learnings" section
    • Apply documented patterns and approaches
    • Avoid repeating mistakes mentioned
    • Build on discovered solutions
  4. Track Continuity:

    • Use TodoWrite to maintain task continuity
    • Reference the handoff document in commits
    • Document any deviations from original plan
    • Consider creating a new handoff when done
  5. Validate Before Acting:

    • Never assume handoff state matches current state
    • Verify all file references still exist
    • Check for breaking changes since handoff
    • Confirm patterns are still valid

Common Scenarios

Scenario 1: Clean Continuation
  • All changes from handoff are present
  • No conflicts or regressions
  • Clear next steps in action items
  • Proceed with recommended actions
Scenario 2: Diverged Codebase
  • Some changes missing or modified
  • New related code added since handoff
  • Need to reconcile differences
  • Adapt plan based on current state
Scenario 3: Incomplete Handoff Work
  • Tasks marked as "in_progress" in handoff
  • Need to complete unfinished work first
  • May need to re-understand partial implementations
  • Focus on completing before new work
Scenario 4: Stale Handoff
  • Significant time has passed
  • Major refactoring has occurred
  • Original approach may no longer apply
  • Need to re-evaluate strategy

Example Interaction Flow

User: /resume_handoff specification/feature/handoffs/handoff-0.md
Assistant: Let me read and analyze that handoff document...

[Reads handoff completely]
[Spawns research tasks]
[Waits for completion]
[Reads identified files]

I've analyzed the handoff from [date]. Here's the current situation...

[Presents analysis]

Shall I proceed with implementing the webhook validation fix, or would you like to adjust the approach?

User: Yes, proceed with the webhook validation
Assistant: This is a bugfix task, so I'll route to the `spark` agent.

[Uses Task tool with subagent_type="spark" and prompt containing:
 - The webhook validation fix task
 - Key learnings from handoff
 - Relevant file:line references
 - Patterns to follow]

[Waits for spark agent to complete]

The spark agent has completed the webhook validation fix. Moving to the next task...

© parcadei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/resume_handoff of parcadei/Continuous-Claude-v3.

Open the folder on GitHubat commit d07ff4b

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in parcadei/Continuous-Claude-v3, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Resume Handoff next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Resume Handoff compared with similar skills
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Resume Handoff this skillparcadei/Continuous-Claude-v33.9k1 repos~2.6kAutomated safety check: PassMIT
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Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Session History Searchslopus/happy24k—~3.1kAutomated safety check: PassMIT
Paseo Agent Handoffgetpaseo/paseo20k1 repos~606Automated safety check: PassCustom licence
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: NotesCustom licence

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Categories

Questions about Resume Handoff

What does Resume Handoff do?

Resume work from handoff document with context analysis and validation. Resume Handoff is an agent skill from parcadei/Continuous-Claude-v3.

When should I use Resume Handoff?

Resume Handoff fits situations like: tasks that involve Session handoff.

How do I install Resume Handoff in Claude Code?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill resume-handoff -a claude-code`. Or copy the skill folder (.claude/skills/resume_handoff in parcadei/Continuous-Claude-v3) into .claude/skills/resume-handoff in your project. Claude Code loads it when a task matches its description.

How do I install Resume Handoff in Codex?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill resume-handoff -a codex`. Or copy the skill folder (.claude/skills/resume_handoff in parcadei/Continuous-Claude-v3) into .agents/skills/resume-handoff in your project. Codex loads it when a task matches its description.

Can I use Resume Handoff in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add parcadei/Continuous-Claude-v3 --skill resume-handoff -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/resume-handoff, .gemini/skills/resume-handoff, .github/skills/resume-handoff and .opencode/skills/resume-handoff in your project.

What does Resume Handoff need to run?

SKILL.md names no scripts, command-line tools or credentials: Resume Handoff is instructions for the agent only.

Does Resume Handoff access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Resume Handoff safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Resume Handoff use?

Resume Handoff is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Resume Handoff use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Resume Handoff?

Skills that share tags, products or a category with Resume Handoff: Orca CLI (stablyai/orca, 89k stars), Beads Task Memory (gastownhall/beads, 28k stars), Session History Search (slopus/happy, 24k stars) and Paseo Agent Handoff (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Resume Handoff?

parcadei (a GitHub user) maintains it in parcadei/Continuous-Claude-v3, which has 3,943 GitHub stars. The repository holds 141 skills in this directory. The repository was last updated on January 26, 2026.

Source: parcadei/Continuous-Claude-v3 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.