AugmentClaude

Checkpoint

Save your progress, decisions, and next steps as a structured snapshot for handoff or later resumption.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.

    This copies the whole skill folder into ~/.claude/skills/checkpoint-pedrohcgs/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
    Sign up to copy
  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Save a structured state snapshot before stopping or handing off. Captures the active plan, recent decisions, file pointers (with line numbers), open questions, and the next 1–3 actions into a checkpoint file under `quality_reports/checkpoints/`. Optionally proposes `[LEARN]` entries to add to MEMORY.md. Use when user says "checkpoint", "save state", "snapshot before I stop", "where am I", "wrap up the session for handoff", or before a long break / model switch / collaborator handoff. Companion to (NOT replacement for) the narrative session-log workflow.

What this skill does

<!-- Pattern adapted from Hugo Sant'Anna's clo-author v4.2.0 (github.com/hugosantanna/clo-author), used with permission. Original /checkpoint shape: project-level session handoff with state snapshot + memory updates. This implementation is reimplemented in original prose against this template's narrative-session-log + plan-on-disk + auto-memory architecture. Attribution credit: Hugo Sant'Anna. -->

/checkpoint — Structured Session Handoff

Produce a state snapshot that the next session (yours, or a collaborator's, or a fresh-context reboot) can resume from in under a minute. The narrative quality_reports/session_logs/ continues to live separately — /checkpoint writes the structured side: facts, file pointers, and next-actions.

When to use

  • Before a long break, model switch (Opus ↔ Sonnet ↔ Haiku), or end of a working day.
  • Before auto-compaction would otherwise discard mid-plan context (paired with the PreCompact hook).
  • Before handing off to a collaborator on the same repo.
  • After completing a chunk of a multi-session plan, when "where am I" is the first question the next session will ask.

When NOT to use

  • For the narrative what happened — that lives in quality_reports/session_logs/ (see .claude/rules/session-logging.md).
  • For commit messages — those go through /commit, which writes its own structured commit body.
  • For decisions about alternatives — those go to templates/decision-record.md via quality_reports/decisions/.

The three artifact types are complementary: session-log = narrative, decision-record = trade-off captured, checkpoint = state to resume from.

Workflow

PHASE 1 — Gather state

Read, in this order:

  1. Most recent planls -t quality_reports/plans/*.md | head -1. Extract: status (DRAFT / APPROVED / COMPLETED), title, top-level files-to-modify list, and any line that begins with "Open questions" / "Risks" / "Next".
  2. Most recent session logls -t quality_reports/session_logs/*.md | head -1. Extract: latest "Next steps" or "Blockers" lines.
  3. MEMORY.md root — read the table of [LEARN] entries already on disk so you don't propose duplicates.
  4. Git stategit log --oneline -20, git status -s, git branch --show-current. Capture: current branch, last 5 subjects, uncommitted file count.
  5. Working filesgit diff --stat HEAD to see which files changed in this session (skip if branch is freshly cut; just say "no in-session edits").
  6. Active TODOs — if a TodoWrite list is in flight in this session, capture the in-progress + next-pending items.

If any of these reads fails (file missing), record "(none on disk)" rather than fabricating content.

PHASE 2 — Write the checkpoint

Write to quality_reports/checkpoints/YYYY-MM-DD_$ARGUMENTS.md (slug from $ARGUMENTS; if no arg, derive from the active plan's title and warn the user). The file uses this template:

---
date: YYYY-MM-DD
branch: [current-branch]
plan: [path to active plan, or "(none)"]
session-log: [path to most recent session log, or "(none)"]
status: in_progress | paused | ready-to-merge
---

# Checkpoint — [short topic]

## Goal (one sentence)
[What this work is trying to accomplish]

## Where I am (one paragraph)
[Last completed step, current step, what's just-not-yet-done. Bullet points OK.]

## File pointers
[Concrete `path:line` references to where the next session should resume. Aim for 3–8.]
- `.claude/skills/checkpoint/SKILL.md:42` — body draft, needs trigger-phrase tightening
- `quality_reports/plans/[slug].md:135` — verification section to refresh after impl
- `CHANGELOG.md` — Unreleased section, v1.8.0 entry not yet drafted

## Recent decisions
[2–5 bullet points of *why* we did what we did this session. Things that wouldn't be obvious from the diff. Skip if none — do not pad.]

## Open questions
[Specific things you'd ask if someone else picked this up. Mark each as Q1, Q2 …]

## Next 1–3 actions
[Imperative form. Concrete. The next session opens this file and starts here.]
1. [...]
2. [...]
3. [...]

## Resume prompt
> Resuming from checkpoint `quality_reports/checkpoints/[filename]`. Read it, then continue with action 1.

Keep the file under ~80 lines. If state is too large for that, the plan file (not the checkpoint) is the right place; checkpoint is a thin index pointing back at the plan.

PHASE 3 — Propose memory updates (skip if --no-memory)

Surface 0–3 candidate [LEARN] entries this session generated. Don't write to MEMORY.md without user approval — this is a propose-then-apply step:

For each candidate, present:

[LEARN:category] proposed: <one-line headline>
Why: <one sentence on what makes this non-obvious>
Apply where: <which future situations would benefit>

If the user says "yes" / "all" / "1 and 3" — append to MEMORY.md (root, the committed one) using the [LEARN] format. If the candidate is machine-specific (paths, tool versions, personal preference), recommend the user route it to .claude/state/personal-memory.md instead per .claude/rules/meta-governance.md.

Stay below 3 candidates. If you have more, the session was probably under-narrated — flag it and recommend a session-log update instead.

PHASE 4 — Output summary

Print, to chat:

✓ Checkpoint saved: quality_reports/checkpoints/YYYY-MM-DD_<slug>.md
  Branch: <branch>     Status: <in_progress|paused|ready-to-merge>
  Active plan: <path or none>     Open questions: <count>
  Resume command: claude --continue   (or paste the file's "Resume prompt" into a fresh session)

If memory candidates were proposed, summarise which (if any) the user accepted.

Cross-references

  • .claude/rules/session-logging.md — narrative companion. Do not duplicate — the checkpoint references the latest session log by path; it does not re-tell the session story.
  • .claude/rules/plan-first-workflow.md — checkpoint reads the active plan; if no plan exists, recommend the user enter plan mode before invoking /checkpoint.
  • templates/decision-record.md — for why we chose A over B, not for where we are.
  • .claude/hooks/pre-compact.py — when CLAUDE_PRECOMPACT_BLOCK_ON_DRAFT=1 is set, the PreCompact hook will block compaction once per DRAFT plan. /checkpoint is the right thing to run when that block fires.

Examples

Example 1 — End-of-day handoff

User says: "checkpoint v180-polisci" Actions:

  1. Read quality_reports/plans/2026-04-27_v180-polisci-apr2026.md (active, DRAFT).
  2. Read quality_reports/session_logs/2026-04-27_v180-polisci-apr2026.md.
  3. Capture: branch feat/v1.8.0-polisci-apr2026, 4 commits ahead of main, 8 files modified.
  4. Write quality_reports/checkpoints/2026-04-27_v180-polisci.md with file pointers to the half-drafted methods-referee.md and the un-started journal-profiles.md poli-sci block.
  5. Propose 1 candidate [LEARN:scope] entry on the linear-cost of disciplinary breadth. Result: Next session: claude --continue, then read quality_reports/checkpoints/2026-04-27_v180-polisci.md and start at action 1.

Example 2 — Mid-plan model switch

User says: "I want to switch to Sonnet for the cheap doc edits — checkpoint first" Actions:

  1. Capture state.
  2. Write checkpoint with status: paused.
  3. Skip memory proposal (small lift — just resuming on a different model). Result: State is on disk; the Sonnet session reads the checkpoint and continues without reloading the full plan.

Troubleshooting

No active plan found. /checkpoint will still write a thin checkpoint with plan: (none), but the right move is usually to enter plan mode first — checkpoints without a plan reference are weak.

Topic-slug missing. If $ARGUMENTS is empty, derive from the active plan filename (strip date prefix). If both are missing, prompt the user for one rather than fabricating.

Output too long. Trim the "Recent decisions" and "Open questions" first. Plans go in plan files; the checkpoint should fit on a screen.

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