gsd-resume-work
Restores full context and active task state from a previous coding session.
Install
mkdir -p .claude/skills/gsd-resume-work-alekseitsvetkov && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15466" && unzip -o skill.zip -d .claude/skills/gsd-resume-work-alekseitsvetkov && rm skill.zipInstalls to .claude/skills/gsd-resume-work-alekseitsvetkov
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Resume work from previous session with full context restorationKey capabilities
- →Restore complete project context
- →Load STATE.md or reconstruct it
- →Detect checkpoints (.continue-here files)
- →Detect incomplete work (PLAN without SUMMARY)
- →Present status visually
- →Route to appropriate next action
How it works
This skill executes the `resume-project` workflow, which loads or reconstructs `STATE.md`, detects checkpoints and incomplete work, presents the project status, and routes to the next context-aware action.
Inputs & outputs
When to use gsd-resume-work
- →Pick up work where I left off
- →Restore project context
- →Resume interrupted task workflow
About this skill
<codex_skill_adapter>
A. Skill Invocation
- This skill is invoked by mentioning
$gsd-resume-work. - Treat all user text after
$gsd-resume-workas{{GSD_ARGS}}. - If no arguments are present, treat
{{GSD_ARGS}}as empty.
B. AskUserQuestion → request_user_input Mapping
GSD workflows use AskUserQuestion (Claude Code syntax). Translate to Codex request_user_input:
Parameter mapping:
header→headerquestion→question- Options formatted as
"Label" — description→{label: "Label", description: "description"} - Generate
idfrom header: lowercase, replace spaces with underscores
Batched calls:
AskUserQuestion([q1, q2])→ singlerequest_user_inputwith multiple entries inquestions[]
Multi-select workaround:
- Codex has no
multiSelect. Use sequential single-selects, or present a numbered freeform list asking the user to enter comma-separated numbers.
Execute mode fallback:
- When
request_user_inputis rejected (Execute mode), present a plain-text numbered list and pick a reasonable default.
C. Task() → spawn_agent Mapping
GSD workflows use Task(...) (Claude Code syntax). Translate to Codex collaboration tools:
Direct mapping:
Task(subagent_type="X", prompt="Y")→spawn_agent(agent_type="X", message="Y")Task(model="...")→ omit.spawn_agenthas no inlinemodelparameter; GSD embeds the resolved per-agent model directly into each agent's.tomlat install time somodel_overridesfrom.planning/config.jsonand~/.gsd/defaults.jsonare honored automatically by Codex's agent router.fork_context: falseby default — GSD agents load their own context via<files_to_read>blocks
Spawn restriction:
- Codex restricts
spawn_agentto cases where the user has explicitly requested sub-agents. When automatic spawning is not permitted, do the work inline in the current agent rather than attempting to force a spawn.
Parallel fan-out:
- Spawn multiple agents → collect agent IDs →
wait(ids)for all to complete
Result parsing:
- Look for structured markers in agent output:
CHECKPOINT,PLAN COMPLETE,SUMMARY, etc. close_agent(id)after collecting results from each agent </codex_skill_adapter>
Routes to the resume-project workflow which handles:
- STATE.md loading (or reconstruction if missing)
- Checkpoint detection (.continue-here files)
- Incomplete work detection (PLAN without SUMMARY)
- Status presentation
- Context-aware next action routing </objective>
<execution_context> @/Users/base/Documents/dem/.codex/get-shit-done/workflows/resume-project.md </execution_context>
<process> **Follow the resume-project workflow** from `@/Users/base/Documents/dem/.codex/get-shit-done/workflows/resume-project.md`.The workflow handles all resumption logic including:
- Project existence verification
- STATE.md loading or reconstruction
- Checkpoint and incomplete work detection
- Visual status presentation
- Context-aware option offering (checks CONTEXT.md before suggesting plan vs discuss)
- Routing to appropriate next command
- Session continuity updates </process>
When not to use it
- →When automatic spawning of sub-agents is not permitted and work needs to be done inline
Limitations
- →Codex has no `multiSelect` for user input
- →Codex restricts `spawn_agent` to cases where the user has explicitly requested sub-agents
- →Requires structured markers in agent output for result parsing
How it compares
This skill automates the restoration of a full project context, including agent interactions and session parameters, enabling smooth continuation of work from a previous session, unlike manually re-establishing context.
Compared to similar skills
gsd-resume-work side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| gsd-resume-work (this skill) | 0 | 3mo | No flags | Intermediate |
| using-superpowers | 95 | 3mo | No flags | Beginner |
| ultrawork | 11 | 2mo | No flags | Advanced |
| clawhub | 25 | 3mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
using-superpowers
obra
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
ultrawork
Yeachan-Heo
Parallel execution engine for high-throughput task completion
clawhub
openclaw
Use the ClawHub CLI to search, install, update, and publish agent skills from clawhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawhub CLI.
skill-installer
openai
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
continuous-learning
affaan-m
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
memory-keeper-proactive-context-maintenance
b4CU-R4U
Automatically detect and maintain memory freshness by monitoring context staleness, significant code changes, task completions, and phase transitions. Proactively suggests and executes memory sync operations with user confirmation. Use when the user says "sync memory", "update context", or when the Skill detects that context is stale (>2 hours), significant changes have occurred (new commits), tasks completed, or major milestones reached. Replaces passive "context is stale" warnings with active maintenance.