Autonomous 技能助手

AI 智能 社区
解读按原文结构重写,命令、链接、术语均保留;右侧可核对作者原始 SKILL.md

方法与流程

  • Step 0 - Read source of truth:Read the approved user request, current plan/spec or work graph, Goal Coverage Contract, Goal Source Drift Guard, active host instructions, .supervibe/memory/ workflow state, recent project memory, CodeGraph health, command-agent plan output, and receipt…
  • Workflow Signal Contract:Every loop status must include workflowSignal so resume, compact context, worktree sessions, and subagent cleanup can distinguish continue, pause, stop/archive, blocked, and complete states.

适用与边界

  • When to Use:Use when a user asks for an autonomous run, epic execution, goal-until-complete loop, long worktree session, or multi-step delivery that must keep working until done or safely stopped.
  • Anti-patterns:Ignoring the boundary: Do not bypass the command or workflow that owns durable loop artifacts. Accepting the rationalization: "One failed task means the whole run should stop"; quarantine the failed task, preserve graph state, and continue only through a…
  • When not to use:Do not bypass the command or workflow that owns durable loop artifacts. Do not use stale context, missing receipts, or legacy migrated evidence as production completion proof.

原文中的明确线索

  • 要点:「This skill is the controller contract for a goal-bounded autonomous run.」、「Boundary: this is the loop controller, not a generic worker-dispatch helper.」、「Accepted graph has independent tasks with disjoint write sets -> dispatch a small parallel wave with explicit worker packets.」、「Tasks share files, public contracts, migrations, or release state -> serialize, split, or quarantine until rollback and ownership are clear.」、「Provider permission, context evidence, receipts, or policy preflight is absent -> policy/readiness stop before non-dry work.」、「Ready work remains after a wave -> continue; do not report final completion from a partial checkpoint.」、「Do not close the loop until every required Goal has accepted evidence or an approved waiver with owner, expiry, impact, and next action.」、「Before dispatch or resume, classify each task, subtask, or emergent issue as include, defer, reject, or spike.」
  • 文件与命令supervibe:dispatching-parallel-agentssupervibe:subagent-driven-development<resolved-supervibe-plugin-root>/docs/references/skill-expert-operating-standard.md.supervibe/memory/includedeferrejectspike

流狐整理:以上内容来自当前 SKILL.md 的章节与原词;未补写作者没有声明的工具、兼容性或能力。

流狐档案 作者与许可取自来源;运行、权限和网络为流狐检测或估算
流狐分类
AI 智能
作者声明 Agent
未找到明确声明;不据此推断已兼容或已测试
静态检查
88 / 100 · 启发式扫描,不代表运行安全
作者 / 版本 / 许可
@vTRKA · 未声明 license
流狐 Token 估算
较高消耗
流狐接入估算
需简单配置
是否需要外部 API Key
未发现要求
检测到的系统要求
macOS · Linux · Windows
底层运行要求
未声明
检测到的文件与系统行为
  • 只读
  • 允许写入 / 修改
  • Shell 执行
检测到的网络行为
仅限本地
安装命令数
无(仅作为资料)

档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。

需要注意: 未限定 allowed-tools,默认拥有全部工具权限。

输出预览 autonomous-agent-loop.preview
# User-facing output

When this skill reports to the user, write the visible summary in the user's current language. Lead with the practical result, blocker, or next decision in 1-3 plain sentences. Keep structured fields, evidence ledgers, command output, and checklist details as supporting material after the summary, not as the whole answer. If the skill emits machine-readable artifacts, keep artifact keys in English but localize the surrounding explanation.

讨论

基于 GitHub Discussions。登录 GitHub 即可参与讨论、点赞、订阅更新。