recall

cursor/plugins

Reconstruct your recent working context from chat history and shared records to resume work efficiently.

What is recall?

Recall mines your chat transcripts and shared records (issue tracker, source control, error logs) to rebuild working context on a topic. Use it when resuming work, catching up on progress, or understanding what you've been working on and where you left off.

Scans recent chat history across your workspace to extract goals, decisions, and open threads
Searches shared records (issue tracker, source control, error tracking) for related bugs, fixes, and user reports
Verifies current state against live git branches and pull requests
Groups findings by thread with status tags (merged, open PR, in flight, reverted, planned)
Surfaces recurring problems and the most useful next action

How to install recall

npx skills add https://github.com/cursor/plugins --skill recall

Claude Code

Cursor

Windsurf

Cline

How to use recall

1.State the topic or feature you want to recall (or ask for recent activity)
2.Specify the time window if needed (default: last 7 days)
3.Confirm the workspace scope
4.The skill will scan your chat transcripts and shared records in parallel
5.Review the returned brief: capsule, thread status, problems, and next move

Use cases

Good for

Resume work on a feature after a break by reconstructing the current state and open threads
Catch up on what happened to a bug across multiple chat sessions and shared records
Understand why a previous fix was reverted and what was tried before
Check the status of a named subsystem or file across your recent work
Start a new session with a tight capsule of where things stand and what to do next

Who it's for

Developers resuming work on ongoing features or bugs
Teams coordinating on shared codebases with distributed chat history
Anyone needing a quick state summary before diving into a task

recall FAQ

What's the difference between recall and just reading my chat history?

Recall scans multiple chat sessions in parallel, cross-references shared records (issues, PRs, error logs) for context you may have missed, and verifies live state against git. It gives you a tight capsule instead of raw transcripts.

Does recall read transcripts from other projects?

No. It defaults to the active workspace and never reads another project's transcripts without being explicitly asked.

What if I already have a full state capsule from the user?

Use it and skip the mining. Recall is for reconstructing context when you don't have it; if you already do, move forward.

How far back does recall search by default?

The last 7 days. You can specify a different window when you invoke it.

What happens if a shared record source (issue tracker, error logs) is unavailable?

Recall reports that source as unavailable and continues with what it can access. Null results are still findings.

Full instructions (SKILL.md)

Source of truth, from cursor/plugins.

name: recall description: "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." disable-model-invocation: true

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.

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.
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".
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.
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.
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.
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.