agentleFS
bnemabnema/pi-pstack/skills/recall/SKILL.md

recall

Skill2 starsChanged 3 months agoMITView on GitHub

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.

We split this skill into the rules it gives an agent

2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 114 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep it tight and on-topic.

    line 11
  2. Distinctive:

    Write the brief to the contract below.

    line 22

“Common” is measured: kept by at least 6 in 10 of the 114 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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. Use for "recall my work on X", "catch me up", "what have I been working on", or "where did I leave off".

Keep it tight and on-topic. Read only what the in-scope threads need, then stop. The heavy reading fans out to parallel subagents. The main thread keeps only their findings and the final brief.

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.

The active Pi transcript is exposed as PI_SESSION_FILE. Its parent directory contains sessions for the active workspace. Never scan other directories under ~/.pi/agent/sessions/; they may contain private chats from unrelated projects. Every session is JSONL.

  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. Resolve PI_SESSION_FILE, then fan out across its sibling sessions with pstack_task when the corpus is large. Give each child a disjoint slice. Order candidates by modification time, search the topic first, read only relevant regions, and skip the current session plus obvious child-agent, eval, and test noise. Each child returns the same schema, one block per session: topic, user goal, decisions, open threads, struggles and corrections, and artifacts such as PRs, tickets, and branches, citing the session filename. For one or two sessions, search directly. Raw transcripts stay in child contexts; the main thread gets 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. A named target carries history you never see in your own transcripts, and that history is the point of the sweep. 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 so you don't reinvent each query vocabulary, 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. A transcript or a stale ticket is history, not current truth, so 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 session filename 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.

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