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subagent-execution-loop

Agent Building
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Orchestrate task execution via fresh subagents with dispatch, monitoring, and result collection

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
Prompt to paste
I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/subagent-execution-loop/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/subagent-execution-loop/. Do not write files or run scripts until I approve.

After I approve, install the complete skill folder, including required referenced files, into that project location. Verify it is discoverable, then tell me its actual invocation name and how to use it. Do not claim it is installed until you have verified it.

Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

Tactic: Subagent Execution Loop

Orchestration Pattern

执行循环直接 load superpowers:subagent-driven-development 当引擎，不再自写循环伪码。 每个任务在引擎内部按以下贯穿规则执行：

  1. Skill load ponytail:ponytail —— 任务开始即开启精简反射。
  2. Skill load superpowers:test-driven-development —— 每任务 RED → GREEN → REFACTOR。
  3. Skill load superpowers:requesting-code-review —— 任务 diff 出来后派 reviewer 子代理。
  4. Skill load ponytail:ponytail-review —— code-review 之后，对 diff 再过一道 过度工程审（delete/stdlib/native/yagni/shrink）。
  5. Skill load superpowers:receiving-code-review —— 核验 review 反馈再落地，反馈错就反驳。

DARE 原生的 implementer-dispatch / execution-monitoring / result-collection 作为 引擎内每任务的派单、盯状态、收结果三步保留。

Decision Criteria

ConditionAction
model 选择 / retry / 超时 / 死锁交给 superpowers:subagent-driven-development 引擎处理
code-review 后先 ponytail:ponytail-review 查过度工程，再 receiving-code-review 落地
Budget < 10% remaining停，报告 partial（DARE 预算治理）
>50% 关键路径 BLOCKED中止执行（DARE 排程判据）

Error Recovery

  • Timeout: Restore from checkpoint, mark task BLOCKED
  • Validation failure: Provide failure reason in retry prompt
  • Deadlock: Analyze dependency graph for unresolvable cycles
  • Budget exhaustion: Produce partial report with remaining task list

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOPWhen to use
execution-monitoringMonitor execution progress, detect anomalies, and report status
implementer-dispatchDispatch execution subagent — select model by complexity, construct prompt with full task context
ponytail:ponytailLazy-senior reflex: simplest thing that holds; mark every deliberate shortcut
ponytail:ponytail-reviewAudit the diff for over-engineering (delete/stdlib/native/yagni/shrink)
result-collectionCollect experiment outputs — metrics, logs, artifacts — into structured result set
superpowers:receiving-code-reviewVerify review feedback before applying; push back when wrong
superpowers:requesting-code-reviewDispatch a code-reviewer subagent after each task
superpowers:subagent-driven-developmentExecute the plan via a fresh subagent per task with two-stage review
superpowers:test-driven-developmentRED -> GREEN -> REFACTOR per task