agentleFS
jrittelmeyerjrittelmeyer/ai-dev-kit/skills/checkpoint/SKILL.md

checkpoint

Skill1 starsChanged 26 days agoMITView on GitHub

Commit and push pending work, then either continue to the next backlog step (context still healthy) or emit a paste-ready resume prompt plus a recommended relaunch model + reasoning effort for a fresh session (context tight). Use when the user says "checkpoint", "commit and continue", "wrap this step up", or asks whether to keep going vs. clear context.

91 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use aside, spinoff and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • TheKREATORSSkill

    aside

    Answer a quick side question without interrupting or losing context from the current task. Resume work automatically after answering.

    Also in 3 projects that use this

  • AhmedMerzaSkill

    spinoff

    After a branch is finished, harvest the work it made CHEAP — the helper you wrote that four other sites now hand-roll, the plumbing that turned a deferred feature small, the pattern that just split the codebase in two. Produces a follow-up backlog (0–3 candidates, feeding /issue), NEVER commits on the current branch. Invoke with /spinoff at the tail of the chain — after /fix-review has settled the review findings, before the MR merges — or when the user asks \"what else should we do while we're here / what did this unlock / anything to follow up on\". This is ship-check's optional twin — that finds what's MISSING and blocks the merge; this finds what's now CHEAP and blocks nothing. Restraint-gated: \"nothing spun off\" is the common and correct answer, and a finding that would have been equally valid before this branch is not a finding.

    Also in 3 projects that use this

  • TheKREATORSSkill

    instinct-export

    Export instincts from project/global scope to a file

    Also in 3 projects that use this

  • seek888Skill

    open-gstack-browser

    Launch GStack Browser — AI-controlled Chromium with the sidebar extension baked in. Opens a visible browser window where you can watch every action in real time. The sidebar shows a live activity feed and chat. Anti-bot stealth built in. Use when asked to "open gstack browser", "launch browser", "connect chrome", "open chrome", "real browser", "launch chrome", "side panel", or "control my browser". Voice triggers (speech-to-text aliases): "show me the browser".

    Also in 5 projects that use this

  • diego-tobalinaSkill

    build-fix

    Fix build and compilation errors systematically. Run when build fails.

    Also in 5 projects that use this

  • seek888Skill

    design-html

    Design finalization: generates production-quality Pretext-native HTML/CSS. Works with approved mockups from /design-shotgun, CEO plans from /plan-ceo-review, design review context from /plan-design-review, or from scratch with a user description. Text actually reflows, heights are computed, layouts are dynamic. 30KB overhead, zero deps. Smart API routing: picks the right Pretext patterns for each design type. Use when: "finalize this design", "turn this into HTML", "build me a page", "implement this design", or after any planning skill. Proactively suggest when user has approved a design or has a plan ready. (gstack) Voice triggers (speech-to-text aliases): "build the design", "code the mockup", "make it real".

    Also in 5 projects that use this

  • +2 more from TheKREATORS
  • +2 more from seek888

The file

We split this skill into the rules it gives an agent

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

  • 0

    Common

    Most of the 85 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Commit + push whatever is pending, then decide: continue to the next step in this session, or hand off cleanly with a resume prompt.

    line 9
  2. Very specific:

    Housekeeping (after push): run the adapter's cache.prune command if defined — local build caches often have no TTL or size cap and grow by …

    line 31
  3. Distinctive:

    Update the project-state memory (what shipped, plan-approval status of the next item), then write the resume prompt to disk and point at it …

    line 59
  4. Very specific:

    Write the full resume prompt (structure below) to the adapter's docs.handoff path if set, else into the agent memory directory as …

    line 64

“Common” is measured: kept by at least 6 in 10 of the 85 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

checkpoint

Commit + push whatever is pending, then decide: continue to the next step in this session, or hand off cleanly with a resume prompt. Never do half of both.

Adapter: .claude/ai-dev-kit.config.json (commit, ci, cache, docs); a missing field → derive it from the repo and say so.

1. Commit & push

  • git status first; stage only the files that belong to the finished work (no blind git add -A if anything unrelated is dirty). If the tree is clean, say so and go to step 2.
  • Message: conventional style matching git log (feat(web): … / chore: …), body = what/why + one-line verification note. Respect the adapter's commit block: trailers: false means no Co-Authored-By trailers; useFileFlag: true means write the message to a scratchpad file and git commit -F <file> (inline -m quoting breaks on PowerShell 5.1).
  • Push. If this checkpoint ends the session (step 2 says hand off), watch CI to green now — provider recipes (find the run for this exact sha → watch → confirm the conclusion via a JSON query, never the stream alone) are in references/ci-watch.md, keyed on the adapter's ci.provider. If instead you're continuing with more work that ends in its own watched CI run, one watch at the end covers the tree.
  • Housekeeping (after push): run the adapter's cache.prune command if defined — local build caches often have no TTL or size cap and grow by gigabytes per build, so pruning at every checkpoint bounds them at the exact cadence they grow (a pre-push hook may backstop it too). No-op when under cap. For a deeper local pass (orphaned dev servers, stale e2e users, dangling Docker images), use the tidy skill.

2. Context-health check

Estimate how much of the window the session has consumed (weigh: count/size of tool results, file dumps, images, long live-verification transcripts) against what the next step costs end-to-end. A full backlog item = re-verify findings → build → full gate → live loop → docs → commit → CI watch: typically a third to half of a fresh window.

  • Healthy: the entire next step fits in the remaining window with ~2× margin → continue (respect plan → sign-off: only build if the plan is already approved).
  • Not healthy / in doubt: hand off. A resume prompt costs a paragraph; a mid-verification compaction costs quality. Borderline counts as not healthy.
  • Three strikes: a session that has failed the same obstacle three times is unhealthy regardless of remaining window — the window is now full of failure and poisons further attempts. Hand off with a diagnosis of the wrong assumption (the fix is to the spec or the context, not another retry); never coach it out in-window — and suggest a retro pass so the obstacle becomes a codified lesson, not a rerun.

State the verdict and the rough numbers behind it — don't decide silently.

3. Handoff (when stopping)

Update the project-state memory (what shipped, plan-approval status of the next item), then write the resume prompt to disk and point at it — disk survives everything, a scrollback paste doesn't, and a fresh session reads a file in targeted chunks instead of ingesting a wall of text:

  1. Write the full resume prompt (structure below) to the adapter's docs.handoff path if set, else into the agent memory directory as resume-prompt.md (one file, overwritten each handoff, index line: "standing resume prompt from the last checkpoint — read when resuming mid-program"). Keep a repo-path handoff out of version control unless the project tracks it deliberately.
  2. Emit the seed — one line: "fresh session: Read <path>, then continue" — plus the same prompt as a fenced paste-ready block for convenience.
  3. End the response with the launch recommendation (rubric below) as the literal last line — Launch: <model> @ <effort> — <why> — it is what the user reads when picking the model for the relaunch. Mirror the same line at the top of the handoff file, right under the title, so it still reaches the user when only the file survives.

Assume the next session starts cold with only CLAUDE.md + memory — anything not in the handoff file, a doc, or memory is lost. The prompt must contain, in order:

  1. Orientation — read the project's status doc + forward backlog (adapter docs.status / docs.backlog); what's shipped, last commit sha(s), CI state.
  2. The next item — id, title, scope, and its sign-off status: if the plan was already approved say so explicitly ("do NOT re-present for sign-off; re-verify the carried findings against the installed dists, then build"); otherwise "present the plan and wait for sign-off".
  3. Carried findings — every load-bearing fact with file:line, each marked verified-where (installed dist vs. read-in-session vs. assumed — the next session re-verifies the assumed ones first instead of rediscovering everything).
  4. Verification expectations — the full gate + the exact live-loop shape, env facts (live keys, Docker containers, free ports, origin-exactness), and which memories to read before editing (name them).
  5. Close-the-loop checklist — docs to tick/update, commit style (per the adapter's commit block), push, the CI-watch commands, and what to propose next before stopping.

The launch recommendation (model × effort)

Spend capability where judgment lives, not where the plan already decided. From the step shape §2 estimated, recommend the cheapest configuration that executes the next step well — name a tier of the harness's current ladder (e.g. Haiku < Sonnet < Opus < Fable, late-2026 — an aging example: verify against the lineup the session actually offers) and a reasoning effort (low → max):

<!-- lint-ok: dated — deliberate example ladder; re-checked each harness-audit -->
  • Mechanical — an approved plan with named files, docs/config-only edits, release chores, gate re-runs: smallest tier that drives the tools reliably, low effort. The plan is the intelligence; the session just executes it.
  • Standard build — a signed-off S/M item around a known design (build → tests → gate → live loop): mid tier, medium effort — high when the diff touches concurrency, authz, or money paths.
  • Judgment — planning or design, audits and scoring, debugging an unknown, adversarial verification of findings: top tier, high effort or above.
  • A mixed next step splits by session: a plan-only session is Judgment; its approved execution relaunches as Mechanical — recommend for the first session-sized chunk and say what the one after relaunches as.
  • In doubt between tiers on work that ships product code or scores quality, take the higher: an oversized model wastes tokens, an undersized one ships plausible-but-wrong work a later session must unwind.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.