MCPInstall

recall

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.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/backnotprop/pstack --skill recall
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads recall automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

Security audits

Independent scans of the skill's instructions and bundled files.

Gen Agent Trust Hub PassSAFE ·The skill is designed to reconstruct work context by reading previous chat history from various agent platforms. While this is its intended purpose, processing historical transcripts introduces a risk of indirect prompt injection where instructions from past sessions could influence the agent's current behavior.
Socket PassNo alerts
Snyk WarnMEDIUM ·Risk: MEDIUM · 1 issue

SKILL.md

The instructions your agent reads when the skill is triggered.

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 where your harness keeps them. Each file is JSONL. Find the active workspace's directory for your harness. If you can't tell which harness you are, check which of these exist for this workspace:

  • Cursor: ~/.cursor/projects/<slug>/agent-transcripts/<uuid>/<uuid>.jsonl. <slug> is the workspace path with the leading slash dropped and each "/" turned into "-" (/Users/you/proj becomes Users-you-proj).
  • Claude Code: ~/.claude/projects/<slug>/<session-id>.jsonl. <slug> is the workspace path with every character that isn't a letter or digit turned into "-" (/Users/you/proj becomes -Users-you-proj).
  • Pi: ~/.pi/agent/sessions/--<slug>--/<timestamp>_<id>.jsonl. <slug> is the workspace path with the leading slash dropped and each "/" turned into "-" (--Users-you-proj--).
  • Codex: ~/.codex/sessions/YYYY/MM/DD/rollout-*.jsonl, not grouped by workspace. Keep only files whose first line has payload.cwd equal to the workspace path.
  • OpenCode: ~/.local/share/opencode/storage/. Sessions are JSON files under session/<project-id>/, with their messages under message/ and part/.
  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. Pick each subagent's reasoning level and fast or standard speed for the job, per the Subagents section of the poteto-mode skill.
  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.

FAQ

What does the recall skill do?

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.

How do I install recall?

Run npx skills add https://github.com/backnotprop/pstack --skill recall in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/recall/ (personal) or .claude/skills/recall/ (project).

Which AI agents can use recall?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is recall safe to install?

Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk flagged items to review. As with any skill, read the SKILL.md and bundled scripts before installing.

Who maintains recall?

It is published by backnotprop in backnotprop/pstack. It has 5,398 recorded installs.

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