gsd-execute-phase
Executes multi-step development plans in parallel phases.
Install
mkdir -p .claude/skills/gsd-execute-phase-acidicsoil && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/12674" && unzip -o skill.zip -d .claude/skills/gsd-execute-phase-acidicsoil && rm skill.zipInstalls to .claude/skills/gsd-execute-phase-acidicsoil
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.
Execute all plans in a phase with wave-based parallelizationKey capabilities
- →Execute plans in a phase
- →Handle user input requests
- →Translate GSD `AskUserQuestion` to Codex `request_user_input`
- →Translate GSD `Task()` to Codex `spawn_agent`
- →Manage multi-select questions
- →Handle `spawn_agent` schema detection
How it works
The skill translates GSD workflow constructs like `AskUserQuestion` and `Task()` into Codex-compatible `request_user_input` and `spawn_agent` calls, managing user interaction and sub-agent execution.
Inputs & outputs
When to use gsd-execute-phase
- →Executing a multi-task development plan
- →Running parallel build or test phases
- →Managing complex agentic workflows
About this skill
<codex_skill_adapter>
A. Skill Invocation
- This skill is invoked by mentioning
$gsd-execute-phase. - Treat all user text after
$gsd-execute-phaseas{{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 or unavailable, activate TEXT_MODE: append--textto{{GSD_ARGS}}so the workflow's built-in text-mode branching takes over. Present everyAskUserQuestioncall as a plain-text numbered list, then stop and wait for the user's reply. Do NOT pick a default and continue (#3018 / #3808). - You may only proceed without a user answer when one of these is true:
(a) the invocation included an explicit non-interactive flag (
--autoor--all), (b) the user has explicitly approved a specific default for this question, or (c) the workflow's documented contract says defaults are safe (e.g. autonomous lifecycle paths). - Do NOT write workflow artifacts (CONTEXT.md, DISCUSSION-LOG.md, PLAN.md, checkpoint files) until the user has answered the plain-text questions or one of (a)-(c) above applies. Surfacing the questions and waiting is the correct response — silently defaulting and writing artifacts is the #3018 failure mode.
C. Task() → spawn_agent Mapping
GSD workflows use Task(...) (Claude Code syntax). Translate to Codex collaboration tools:
Schema detection (required first step): Codex exposes two spawn_agent schemas:
- agent_type-capable schema (e.g.
multi_agent_v2):spawn_agentacceptsagent_type,message,reasoning_effort,fork_context, etc. — typed GSD agent dispatch is available. - Generic schema (
multi_agent_v1):spawn_agentaccepts onlymessage,items,fork_context— there is noagent_typefield. Typed GSD agent dispatch is unavailable in this session.
Before spawning, inspect the spawn_agent tool's visible parameter schema (via tool_search or the tool list) to determine which form is active.
Typed mapping (agent_type-capable schema only):
Task(subagent_type="X", prompt="Y")→spawn_agent(agent_type="X", message="Y")Agent(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.- Resolved
reasoning_effort="low|medium|high|xhigh"(xhighis a GSD/Codex tier, not a generic runtime enum) → passreasoning_efforttospawn_agentwhen the runtime/tool supports it. Omit missing, empty, inherited, or unsupported values; do not invent one-off effort literals in workflow prose. fork_context: falseby default — GSD agents load their own context via<files_to_read>blocksTask(isolation="worktree")/Agent(isolation="worktree")→ no direct Codex mapping. Codexspawn_agentdoes not create or bind a git worktree automatically. Workflows that require this isolation must fail closed or use an explicit manual worktree protocol before spawning (#3360).
Generic-agent workaround (multi_agent_v1 schema — NO agent_type field):
When only the generic multi_agent_v1 schema is available, typed GSD agent dispatch
(gsd-planner, gsd-executor, etc.) is NOT possible. This is a known Codex limitation
(openai/codex#15250). This workaround is NOT equivalent to typed gsd-planner/gsd-executor
execution — GSD agents carry project-aware prompts, audit logging, and workflow context
that a generic subagent lacks. Use the following fallback:
- Resolve your active Codex config root — the directory that contains your
config.toml. This directory is determined in priority order:$CODEX_HOME(if set), the path given by--config-dir(if passed on invocation), a local.codexdirectory in the current project (if--localwas used), or the default global config directory. Readagents/<agent-name>.tomlrelative to that config root to extract the agent's system instructions. - Inject those instructions as a role-preamble into a generic
spawn_agent(message=...)call. - Label results and logs clearly as "generic-agent workaround" so the orchestrator and user know full typed-agent guarantees are not in effect.
- Where typed dispatch is mandatory for correctness (e.g. worktree isolation), fail closed and report the schema limitation rather than silently degrading.
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. - In some Codex sessions, multi-agent tooling can be deferred. If
spawn_agentis not currently visible, discover tools first viatool_searchbefore defaulting to inline execution.
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>
Orchestrator stays lean: discover plans, analyze dependencies, group into waves, spawn subagents, collect results. Each subagent loads the full execute-plan context and handles its own plan.
Optional wave filter:
--wave Nexecutes only WaveNfor pacing, quota management, or staged rollout- phase verification/completion still only happens when no incomplete plans remain after the selected wave finishes
Flag handling rule:
- The optional flags documented below are available behaviors, not implied active behaviors
- A flag is active only when its literal token appears in
{{GSD_ARGS}} - If a documented flag is absent from
{{GSD_ARGS}}, treat it as inactive
Context budget: ~15% orchestrator, 100% fresh per subagent. </objective>
<execution_context> @/home/user/projects/temp/ai-apps/.personal-projects/registry-atlas/.codex/gsd-core/workflows/execute-phase.md @/home/user/projects/temp/ai-apps/.personal-projects/registry-atlas/.codex/gsd-core/references/ui-brand.md </execution_context>
<runtime_note>
Copilot (VS Code): Use vscode_askquestions wherever this workflow calls AskUserQuestion. They are equivalent — vscode_askquestions is the VS Code Copilot implementation of the same interactive question API.
</runtime_note>
Available optional flags (documentation only — not automatically active):
--wave N— Execute only WaveNin the phase. Use when you want to pace execution or stay inside usage limits.--gaps-only— Execute only gap closure plans (plans withgap_closure: truein frontmatter). Use after verify-work creates fix plans.--interactive— Execute plans sequentially inline (no subagents) with user checkpoints between tasks. Lower token usage, pair-programming style. Best for small phases, bug fixes, and verification gaps.
Active flags must be derived from {{GSD_ARGS}}:
--wave Nis active only if the literal--wavetoken is present in{{GSD_ARGS}}--gaps-onlyis active only if the literal--gaps-onlytoken is present in{{GSD_ARGS}}--interactiveis active only if the literal--interactivetoken is present in{{GSD_ARGS}}- If none of these tokens appear, run the standard full-phase execution flow with no flag-specific filtering
- Do not infer that a flag is active just because it is documented in this prompt
Context files are resolved inside the workflow via node "$HOME/.codex/gsd-core/bin/gsd-tools.cjs" query init.execute-phase and per-subagent <files_to_read> blocks.
</context>
When not to use it
- →When `request_user_input` is rejected or unavailable and no non-interactive flag is present
- →When `spawn_agent` is restricted and automatic spawning is not permitted
Limitations
- →Codex has no `multiSelect` for questions
- →Codex `spawn_agent` does not create or bind a git worktree automatically
- →Codex restricts `spawn_agent` to cases where the user has explicitly requested sub-agents
How it compares
This skill provides a specific adapter for GSD workflows within Codex, enabling automated execution and interaction that would otherwise require manual translation or intervention.
Compared to similar skills
gsd-execute-phase side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| gsd-execute-phase (this skill) | 0 | 1mo | No flags | Advanced |
| workflow-automation | 3 | 6mo | Review | Intermediate |
| workflow-execute | 1 | 4mo | Review | Advanced |
| lfg | 0 | 2mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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