checkpoint

checkpoint is a skill for Claude Code, Codex from synaptiai/agent-capability-standard. It costs 37 tokens per session (2,439 once invoked), scanned A, original, Apache-2.0.

A skill for creating a restorable marker before changing files, running a plan, or carrying out another potentially irreversible action. It supports backups such as Git stashes, file copies, state snapshots, and database savepoints.

In plain words
What is it for?
Use it before mutations or execution steps to record the affected scope, the reason, the restore method, and optionally an expiry time.
Why use it?
It gives the agent a way to return to an earlier state if a later operation causes problems.

Skill for Claude CodeCodex

Part of the agent-capability-standard plugin — 42 skills, 2 hooks shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/synaptiai/agent-capability-standard/checkpoint
Any agent
npx skills add synaptiai/agent-capability-standard --skill checkpoint
Clone the repo
git clone --depth 1 https://github.com/synaptiai/agent-capability-standard

Made for: Claude Code, Codex.

Or install agent-capability-standard, the plugin that ships this one along with the rest of its 42 skills, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for checkpoint

README.md
[![agentmods](https://agentmods.dev/badge/skills/synaptiai/agent-capability-standard/checkpoint.svg)](https://agentmods.dev/skills/synaptiai/agent-capability-standard/checkpoint)
Your own site
<a href="https://agentmods.dev/skills/synaptiai/agent-capability-standard/checkpoint"><img src="https://agentmods.dev/badge/skills/synaptiai/agent-capability-standard/checkpoint.svg" alt="Measured on agentmods" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,439 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00037 $0.02439
Opus 5 $0.00018 $0.01220
Sonnet 5 $0.00007 $0.00488
Haiku 4.5 $0.00004 $0.00244

Measured 4d ago against content hash fbb05b6169b5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

checkpoint scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/checkpoint/SKILL.md · 273 lines

How it starts

The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Intent

Execute checkpoint to create a restorable state marker before any mutating operation. This is the foundation of safe agentic execution - enabling rollback if subsequent actions fail.

Success criteria:

  • Checkpoint successfully created with unique identifier
  • All files/state in scope are captured
  • Restore command is documented and tested
  • Expiry policy set if applicable

Compatible schemas:

  • schemas/output_schema.yaml

Inputs

Parameter Required Type Description
scope Yes string|array Files, directories, or state keys to checkpoint
reason No string Why this checkpoint is being created (for audit trail)
checkpoint_type No enum Type: git_stash, file_backup, state_snapshot, database_savepoint
expiry No string When checkpoint can be garbage collected (e.g., "24h", "never")

Procedure

  1. Identify scope: Determine exactly what needs to be checkpointed

    • List all files that will be modified by upcoming mutation
    • Include related configuration or state files
    • Check for uncommitted git changes in scope
  2. Select checkpoint type: Choose appropriate mechanism

    • git_stash: For git-tracked files (preferred for code changes)
    • file_backup: For non-git files, copy to .checkpoints/
    • state_snapshot: For in-memory or runtime state
    • database_savepoint: For database transactions
  3. Capture pre-mutation state: Execute the checkpoint

    • For git: git stash push -m "checkpoint:<id>:<reason>"
    • For files: Copy to .checkpoints/<id>/ with manifest
    • Record hashes of all captured content
    • Verify checkpoint integrity immediately after creation
  4. Generate restore command: Document how to rollback

    • Exact command(s) to restore state
    • Any prerequisites for restoration
    • Order of operations if multiple systems involved
  5. Ground claims: Attach evidence of checkpoint creation

    • Format: tool:bash:<command>, file:<checkpoint_path>
    • Include hash verification output

Read the full file on GitHub · 273 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 273 lines · 37 tokens per session scan A fbb05b6169b5

Subscribe to this mod's changes

checkpoint is a skill published in the GitHub repository synaptiai/agent-capability-standard (4 stars, last pushed 4d ago), licensed Apache-2.0. It adds 37 tokens to every session and 2,439 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

gh

GitHub API access and project management automation for the hallucination-detector repo. Uses octokit with proxy-aware client for all GitHub operations — issues, PRs, labels, milestones, Projects V2. No gh CLI required.

bitflight-devops/hallucination-detector · 49 tokens

evaluate-options

Research and evaluate implementation options before presenting a recommendation. Use when multiple approaches exist for a problem and a decision is needed. Launches one background research agent per option in parallel, collects evidence-backed findings, then presents a recommendation grounded in observed data — not…

bitflight-devops/hallucination-detector · 97 tokens

delegate

Quick delegation template for sub-agent prompts. Use when assigning work to a sub-agent, before invoking the Task tool, or when preparing prompts for specialized agents. Provides the WHERE-WHAT-WHY framework. For comprehensive delegation guidance, activate the agent-orchestration how-to-delegate skill.

bitflight-devops/hallucination-detector · 60 tokens

beginner-tone

코딩도 AI도 처음인 초보자와 대화할 때 쓰는 말투·안전 지침. SoDamHarness 설치 시 자동 활성화.

sodam-ai/SoDam-Harness-Eng · 34 tokens

ai-safe-driver

Use when the agent keeps repeating a mistake, ignores a correction, retries a failed tool unchanged, breaks an output format again, drifts from the latest request, or makes excuses instead of diagnosing recurrence. Also use for a conversation health check, compaction decision, or new-session question.

ssauma/ai-safe-driver · 61 tokens

sodam-harness-self-check

작업을 끝내거나 "다 됐어요"라고 말하기 전에 실제로 작동하는지 점검하고 증거를 보여줄 때 사용. 위험·중요 작업 마무리, 완료 선언, 검증 요청 시 적용.

sodam-ai/SoDam-Harness-Eng · 51 tokens