gsd-resume-work

Pass

Resume work from previous session with full context restoration

@juaniitos
MIT4/8/2026
(0)
0
0
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Install Skill

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Install globally (user-level):

npx skillhub install juaniitos/AnyoneAIInterviewerBackend/gsd-resume-work

Install in current project:

npx skillhub install juaniitos/AnyoneAIInterviewerBackend/gsd-resume-work --project

Suggested path: ~/.claude/skills/gsd-resume-work/

SKILL.md Content

---
name: "gsd-resume-work"
description: "Resume work from previous session with full context restoration"
metadata:
  short-description: "Resume work from previous session with full context restoration"
---

<codex_skill_adapter>
## A. Skill Invocation
- This skill is invoked by mentioning `$gsd-resume-work`.
- Treat all user text after `$gsd-resume-work` as `{{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` → `header`
- `question` → `question`
- Options formatted as `"Label" — description` → `{label: "Label", description: "description"}`
- Generate `id` from header: lowercase, replace spaces with underscores

Batched calls:
- `AskUserQuestion([q1, q2])` → single `request_user_input` with multiple entries in `questions[]`

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_input` is 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 (Codex uses per-role config, not inline model selection)
- `fork_context: false` by default — GSD agents load their own context via `<files_to_read>` blocks

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>

<objective>
Restore complete project context and resume work seamlessly from previous session.

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/diegocaminor/Documents/proyectos/anyone-ai/final-project/AnyoneAIInterviewerBackend/.codex/get-shit-done/workflows/resume-project.md
</execution_context>

<process>
**Follow the resume-project workflow** from `@/Users/diegocaminor/Documents/proyectos/anyone-ai/final-project/AnyoneAIInterviewerBackend/.codex/get-shit-done/workflows/resume-project.md`.

The workflow handles all resumption logic including:

1. Project existence verification
2. STATE.md loading or reconstruction
3. Checkpoint and incomplete work detection
4. Visual status presentation
5. Context-aware option offering (checks CONTEXT.md before suggesting plan vs discuss)
6. Routing to appropriate next command
7. Session continuity updates
   </process>