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Manage durable working-session memory for coding agents.
Passed 4 of 12 test cases with the skill, and 5 of 12 without it.
2 fixed6 passed either way11 still failing3 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
You just read `handoff.md` from a previous session folder, which states that `src/main.py` was updated and unit tests passed. What verification step must you perform before editing the next file?
| Checked | Without skill | With skill |
|---|---|---|
| Verifies the claimed repository state using git status or targeted file checks before taking action | Missed | Passed |
The instructions your model reads when the skill loads.
Keep a durable, human-readable record of the current working session so another agent can resume after a disconnect with minimal context loss.
Use this skill when:
./session/ directories.Create one directory per working session:
mkdir -p session
date +%Y%m%d_%H%M%S
mkdir -p session/<session_date_time>
Use local time from the machine. Reuse the same session directory for all checkpoints in the same conversation unless the user explicitly starts a new session.
Expected files:
session_state.md - overall goal, current subtask, loaded skills, status, plan, assumptions, blockers, and next actions.timeline.md - append-only log of major actions, commands, results, and decisions.files.md - files inspected, files changed, and why they matter.handoff.md - concise resume instructions for the next agent.Add other files only when useful, such as experiments.tsv, review_notes.md, or copied command logs.
At the start of a session:
ls -dt session/* 2>/dev/null | head
test cases passed, vs 5 / 12 without
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