Recall

作者 cursorccb5507cec15無授權條款10K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a tight current-state brief. Use for 'recall my work on X', 'catch me up', 'what have I been working on', 'where did I leave off', before starting or resuming work.

AI 產生的概覽

從聊天記錄與共享紀錄重建近期工作脈絡,並回傳一份精簡的現況簡報。

功能
Recall 透過挖掘本機聊天記錄來重建使用者近期的工作脈絡;當指定了主題時,還會檢索共享紀錄中的使用者回報、先前的修正與事故。它會用即時狀態核對浮現的分支、PR 與工單,然後撰寫一份簡報,包含重點摘要、帶狀態標籤的執行緒、反覆出現的問題,以及一個具體的下一步行動。此技能僅包含指示,不附帶指令碼。
適用情境
適用於開始或恢復工作之前,或被要求回想某主題的工作、掌握近況、確認上次進行到何處時。它不適用於恢復某一個特定的先前對話、把習慣固化為技能,或產出人類可讀的工作總結。
執行需求
需要存取 Cursor 專案目錄下的本機聊天記錄檔案,以及用於核對分支、PR 與工單的 git 與 gh。共享紀錄檢索依賴獨立的 why 技能及其來源調查器,涵蓋原始碼控管、問題追蹤器、聊天與問題頻道、文件與錯誤追蹤,其中部分 MCP 來源可能無法使用。

Recall

Before you start or resume work, you rebuild the user's recent working context and hand back a tight capsule of where things stand now and what to do next.

Keep it tight and on-topic. Read only what the in-scope threads need, then stop.

Your context lives in two records. Your own chat history holds what you did and decided. The shared record holds everything that happened around the same code under other names: the symptoms users keep reporting, the fixes that shipped and got reverted, the errors still firing in prod. That second record is what the why skill searches, across source control, the issue tracker, chat and issue channels, long-form docs, and error tracking. A feature with a long bug tail keeps most of its story there, so don't reconstruct it from your transcripts alone.

Transcripts live at ~/.cursor/projects/<slug>/agent-transcripts/<uuid>/<uuid>.jsonl, where <slug> is the workspace path with the leading slash dropped and each "/" turned into "-" (so /Users/you/proj becomes Users-you-proj). Every line is one chat message.

  1. Classify, then route. One specific prior chat to resume is the session-pickup playbook, not this. Turning habits into a durable skill is automate-me. A human-readable summary of your work is a different task. Recall loads working context across recent chats before you act. If the user already gave you a full state capsule (paths, branch, the change), use it and skip the mining.
  2. Lock the scope before searching. Pin the window ("recent" is a real range, default the last 7 days), the topic if named, and the workspace (default the active one. Never read another project's transcripts without being asked). State the scope back. Never quietly turn "all" into "recent N".
  3. Fan out across your chat history. Spawn parallel subagents on a fast, cheap model, each taking a slice of the corpus. Tell every subagent to order candidates by real modification time (ls -t) and never by UUID name, grep the topic first and then read only the matching chats and only their relevant regions, and skip the current chat plus obvious noise (subagent, eval, and test chats). Each returns the same schema, one block per chat: topic, the user's goal, decisions, open threads, struggles and corrections, and artifacts (PRs, tickets, branches), each citing the chat UUID. For one or two chats, skip the fan-out and search directly. The raw transcripts stay in the subagents. The main thread gets only their findings.
  4. Sweep the shared record whenever the topic names a feature, file, subsystem, area, or bug. This is the default, not a judgment call, and "my work on X" does not exempt it. Hand it to the why skill's source investigators, but steer their question from "why was this built this way" to "what's the current state, what's been tried and didn't hold, and what are users still reporting". Reuse its per-source playbooks, run the investigators in parallel with the chat-history mining, and inherit its posture: one investigator per source, null results are findings, skip an unavailable MCP and say so. Fold what comes back into the brief. Skip this step only for pure activity recall with no named target ("what did I do this week"), where your own history and live state are the entire answer.
  5. Verify against live state. Take the PRs, branches, and tickets that the mining and the sweep surfaced and check them with git and gh. When the answer hinges on what an agent actually did (the tools it ran, files it read, errors it hit), read the full transcript, not just a trimmed local copy.
  6. Write the brief to the contract below. Group by thread. Stay on the named topic.

Output contract

Lead with the capsule, then the thread status, then the problems, then the next move. Deeper detail goes below or gets cut.

  • Capsule. At most 5 bullets. What this work is and where it stands overall.
  • Threads. One line each, prefixed with exactly one status tag: [merged #N], [open PR #N], [in flight <branch>], [verified, uncommitted], [reverted #N], or [planned, not started]. A thread with no tag is not done yet, so tag it.
  • Problems. At most 5, the recurring ones. Include the symptoms users keep reporting and any fix that shipped and was reverted, so the next attempt starts where the last one failed.
  • Next move. The single most useful next action, concrete.

An adjacent feature or ticket stays out unless it blocks this one. When the capsule and thread lines outgrow a screen, cut detail before you cut threads. Write the brief through the unslop skill, cite chat findings by UUID and shared-record findings by their source (PR #, ticket ID, chat permalink, error-tracker issue), and sanitize private context before any public output.

Reply: the brief, to the contract above.

來源與署名

來源:cursor/plugins位於pstack/skills/recall提交ccb5507

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