Borrowing it
Nothing to install: this file belongs to xiaojilele-glitch/WhyBuddy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xiaojilele-glitch/WhyBuddy/main/.kiro/steering/task-autopilot-repo-alignment-2026-04-23.mdgit clone --depth 1 https://github.com/xiaojilele-glitch/WhyBuddyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/xiaojilele-glitch/whybuddy/task-autopilot-repo-alignment-2026-04-23)<a href="https://agentmods.dev/instructions/xiaojilele-glitch/whybuddy/task-autopilot-repo-alignment-2026-04-23"><img src="https://agentmods.dev/badge/instructions/xiaojilele-glitch/whybuddy/task-autopilot-repo-alignment-2026-04-23/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/xiaojilele-glitch/whybuddy/task-autopilot-repo-alignment-2026-04-23"><img src="https://agentmods.dev/badge/instructions/xiaojilele-glitch/whybuddy/task-autopilot-repo-alignment-2026-04-23.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.06198 | $0.06198 |
| Opus 5.5 | $0.02479 | $0.02479 |
| Sonnet 5.5 | $0.01240 | $0.01240 |
| Haiku 4.5 | $0.00620 | $0.00620 |
Grade A, and why
WhyBuddy task-autopilot-repo-alignment-2026-04-23.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
任务自动驾驶与现有仓库对齐关系(2026-04-23)
2026-04-26 增补:Phase 1 已闭合
本文件原始判断仍然成立:task-autopilot 是现有 mission-first 主仓之上的产品投影层,不是第二套事实源。
但当前状态已经从“18 份 specs 待实现”推进为:
18 / 18specs 已完成并收口54 / 54markdown 已完成345 / 345顶层任务项已闭合602 / 602raw checklist 已闭合- 第一条 compatibility-first 代码纵切已进入主线
当前已经落地的对齐锚点:
Mission -> Destinationshared/mission/autopilot.ts的parseMissionDestination()与MissionAutopilotSummary.destination
Workflow / Mission stage -> Route- autopilot route summary、candidate route、route selection / replan 字段
Runtime state -> Drive StateinferMissionAutopilotDriveState()与 server projection
Decision / HITL -> Takeover- takeover summary、decision prompt、missing-info clarifications、operator actions
Runtime facts -> Evidence / Explanation- evidence timeline、correlation index、recommendation details、remaining steps
仍需保持的边界:
- 不宣称开放域 L5。
- 不把 projection 等同于完整 runtime 自动化。
- 不以产品对象重命名替代 Mission / Workflow / Runtime 的事实主干。
- 下一阶段重点应转向 runtime 行为深化:parser 版本化、route planner 自动编队、fleet orchestration、takeover governance、evidence replay trust chain 与 success metrics。
目的
这份文档用于回答一个实际问题:task-autopilot 的 18 份 specs,不应该被理解成“另起一套新的任务平台”,而应该被理解成对现有 mission-first 主仓的一层上位产品抽象。
本文重点说明三件事:
task-autopilot与现有README、project-overview、Mission Runtime、workflow runtime、HITL、replay、audit、lineage、Web-AIGC主线分别如何对齐。- 哪些 specs 主要是在复用现有底座做“产品投影和界面收口”。
- 哪些 specs 虽然已有部分基础,但本质上仍属于待实现能力,不能写成“仓库已经完成”。
本文坚持一个前提:compatibility-first。
Compatibility-First 结论
1. task-autopilot 是上位叙事,不是第二套事实源
当前仓库的事实主干已经很明确:
README与README.zh-CN把产品定位为 mission-first 的任务操作系统。.kiro/steering/project-overview.md把系统主干定义为办公室主壳、任务工作台、Mission Runtime、workflow runtime、replay / audit / lineage 与 Web-AIGC 主线能力的组合。Mission Runtime、workflow runtime、HITL、replay、audit、lineage、Web-AIGC都已经有各自的契约、路由、事件和测试证据。
因此,task-autopilot 更适合做成:
- 产品层:
Destination / Route / Drive State / Fleet / Takeover - 工程层:继续保留
mission / workflow / runtime / decision / replay / audit - 中间层:通过映射、投影、聚合和 UI 收口把两层连接起来
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 327 lines · 6,198 tokens per session scan A 59334035373c
WhyBuddy task-autopilot-repo-alignment-2026-04-23.md is an instructions file published in the GitHub repository xiaojilele-glitch/WhyBuddy (380 stars, last pushed 1mo ago), licensed MIT. It adds 6,198 tokens to every session, about $0.0248 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-23.
WhyBuddy task-autopilot-repo-alignment-2026-04-23.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| WhyBuddy task-autopilot-repo-alignment-2026-04-23.mdxiaojilele-glitch/WhyBuddy | Instructions file | 380 | 1mo ago | MIT | A | 6,198 | Kiro |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |