원클릭으로
at-prompt-creator
Create agent-team orchestrated prompt bundles (orchestrator + sub-prompts) and store them through prompt-manager.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Create agent-team orchestrated prompt bundles (orchestrator + sub-prompts) and store them through prompt-manager.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Check AI CLI usage/quota for Claude Code, OpenAI Codex, Google Gemini CLI, Z.AI, and Synthetic. Use when user asks about remaining quota, usage limits, rate limits, or wants to check how much capacity is left.
Detect installed AI coding CLIs and local model providers; outputs a cached JSON inventory for routing (/detect-clis).
Execute prompts from ./prompts/ directory with various AI models. Use when user asks to run a prompt, execute a task, delegate work to an AI model, run prompts in worktrees/tmux, or run prompts with verification loops.
Orchestrate multi-prompt execution with phase groups, optional auto-deps, and model-tiered agent roles.
Read and manage daplug configuration from CLAUDE.md using <daplug_config> blocks, with legacy fallback and migration support.
Automated sprint planning and execution from technical specifications (prompt generation, dependency planning, stateful execution)
| name | at-prompt-creator |
| description | Create agent-team orchestrated prompt bundles (orchestrator + sub-prompts) and store them through prompt-manager. |
| allowed-tools | ["Bash(python3:*)","Bash(jq:*)","Bash(cat:*)","Bash(printf:*)","Bash(mkdir:*)","Read","Write","Edit","Task","Grep","Glob"] |
Create an orchestrated prompt set for complex work:
Use this skill when the user asks for /create-at-prompt.
/create-prompt)./prompts/ (never completed/)PLUGIN_ROOT=$(jq -r '.plugins."daplug@cruzanstx"[0].installPath' ~/.claude/plugins/installed_plugins.json)
PROMPT_MANAGER="$PLUGIN_ROOT/skills/prompt-manager/scripts/manager.py"
CONFIG_READER="$PLUGIN_ROOT/skills/config-reader/scripts/config.py"
Use prompt-manager for all prompt writes/reads. Do not create files manually.
Break the task into sub-prompts only when at least one of these is true:
Keep sub-prompts single-purpose and executable in isolation.
Create sub-prompts first so orchestrator delegation can reference exact prompt IDs.
For each sub-task:
python3 "$PROMPT_MANAGER" create "<subtask-name>" --folder "$FOLDER" --content "$SUB_PROMPT_CONTENT" --json
Each sub-prompt must include:
<objective><scope><output> files<verification> criteriaAfter sub-prompts exist, create one orchestrator prompt that references them.
Use this template structure:
<objective>
Coordinate multi-agent execution for the parent task using existing sub-prompts.
</objective>
<orchestration>
<phase name="plan">
<!-- Claude native planning and risk check -->
- Confirm assumptions, dependencies, and execution strategy.
- Draft exact Task() orchestration with explicit escalation paths.
</phase>
<phase name="execute" strategy="parallel|sequential">
<!-- Delegation to sub-prompts via /run-prompt -->
<delegate prompt="228a" model="opencode" flags="--worktree" />
<delegate prompt="228b" model="codex" flags="--worktree --loop" />
</phase>
<phase name="validate">
<!-- Claude native integration + merge criteria -->
- Verify outputs are consistent and conflict-free.
- Resolve overlaps before final handoff.
</phase>
</orchestration>
<merge_criteria>
- All sub-prompts completed or explicitly triaged.
- No unresolved file conflicts.
- Validation checks pass.
</merge_criteria>
<output>
- Final integrated summary
- Recommended /run-at-prompt group syntax
</output>
The orchestrator body should include explicit Task() delegations so it is executable:
Task(
subagent_type: "at-monitor",
model: "haiku",
run_in_background: true,
prompt: "Launch /run-prompt 228a --model opencode --worktree and return Execution Report format."
)
Create orchestrator prompt:
python3 "$PROMPT_MANAGER" create "<task-name>-orchestrator" --folder "$FOLDER" --content "$ORCHESTRATOR_CONTENT" --json
After prompt creation, present:
/run-prompt <orchestrator-id> --model claude
/run-at-prompt "220,221 -> 222" --model codex --worktree
/run-at-prompt "220 221 222" --auto-deps --dry-run
Recommend --worktree for any parallel execution. Recommend --loop for high-risk prompts.
/run-prompt only; no ambiguous free-form delegation.<task>-orchestrator<task>-backend<task>-frontend<task>-tests<task>-docs