synthesis-checkpoint

synthesis-checkpoint is a skill for Claude Code, Codex from synthesisengineering/synthesis-skills. It costs 47 tokens per session (3,393 once invoked), scanned A, original, Apache-2.0.

A procedure for refreshing an agent's understanding during a long coding session. It checks the current date, project files, recent Git history, and claims from other active sessions.

In plain words
What is it for?
Use it when you need to checkpoint, re-sync, recover after context compression, refresh project state, or verify that dates and recent changes are still correct.
Why use it?
Long sessions and context compression can make an agent rely on outdated information. Rechecking the project reduces mistakes caused by that drift.

Skill for Claude CodeCodex

Written for Claude Code and Codex: SessionStart hook event, but also agents/openai.yaml present. Also seen: mentions subagents; mentions Claude Code; mentions Codex.

Part of the synthesis-skills plugin — 63 skills, 4 hooks shipped together

Good fit Use it when you need to checkpoint, re-sync, recover after context compression, refresh project state, or verify that dates and recent changes are still correct.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/synthesisengineering/synthesis-skills/synthesis-checkpoint
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.

Any agent
npx skills add synthesisengineering/synthesis-skills --skill synthesis-checkpoint
Clone the repo
git clone --depth 1 https://github.com/synthesisengineering/synthesis-skills

Made for: Claude Code, Codex.

Or install synthesis-skills, the plugin that ships this one along with the rest of its 63 skills, 4 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 synthesis-checkpoint

README.md
[![agentmods](https://agentmods.dev/badge/skills/synthesisengineering/synthesis-skills/synthesis-checkpoint/github.svg)](https://agentmods.dev/skills/synthesisengineering/synthesis-skills/synthesis-checkpoint)
Your own site
<a href="https://agentmods.dev/skills/synthesisengineering/synthesis-skills/synthesis-checkpoint"><img src="https://agentmods.dev/badge/skills/synthesisengineering/synthesis-skills/synthesis-checkpoint/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for synthesis-checkpoint

Your own site · 80×15
<a href="https://agentmods.dev/skills/synthesisengineering/synthesis-skills/synthesis-checkpoint"><img src="https://agentmods.dev/badge/skills/synthesisengineering/synthesis-skills/synthesis-checkpoint.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,393 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00047 $0.03393
Opus 5 $0.00023 $0.01697
Sonnet 5 $0.00009 $0.00679
Haiku 4.5 $0.00005 $0.00339

Measured today against content hash 0c31c179d9b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

synthesis-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 today.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/refresh.py, scripts/test_refresh.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/synthesis-checkpoint/SKILL.md · 282 lines

How it starts

The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Synthesis Checkpoint — Mid-Session Refresh & Drift Recovery

Refresh-and-report mode

When asked to refresh after an ecosystem upgrade or report session readiness, load this skill from the current verified installed root, then follow references/refresh-and-report.md. This mode uses a deterministic local inspector and optional campaign feedback. Project feedback destinations follow explicit registry successor links; the reporting session keeps its project identity and execution restrictions. It ends after reporting and grants no project implementation or repair authority. Ordinary checkpoints use the protocol below and do not send campaign feedback.

Current skill text and a native runtime reload are distinct evidence. Never equate an old in-context skill body with a failed current startup, or copying new files with proof a running harness reloaded them.

The Problem

LLMs are stateless at the model level. Across a long conversation, an LLM's sense of "what's true now" can drift from what's actually on disk and in git. Drift sources:

  • Time drift. The model has no clock. If the conversation started Tuesday and continues Wednesday, the model often still thinks it's Tuesday.
  • State drift. Project CONTEXT.md may have been edited (by user, by sub-agent, by another session) since the model last read it.
  • Compaction drift. When the context window approaches its limit, the harness may summarize older turns. Details disappear. The model often cannot detect that this happened.
  • Cached-fact drift. Facts the model read earlier in the conversation (last commit, last session date, last decision) may no longer be true.
  • Coordination drift. Another live root session may have claimed or changed the same source area since the last tool call.

Self-discipline degrades with conversation length. Rules read at session start lose salience as turns accumulate. Even a model that "knows" to verify often skips verification under the weight of accumulated context.

Read the full file on GitHub · 282 lines

Files

What ships with it

4 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. today Changed · +24 lines 0c31c179d9b3
  2. 2d ago Changed · +36 lines · -71 tokens per session 7ed7902e82c5
  3. 10d ago First seen · 222 lines · 118 tokens per session scan A c9402bb5b9d6

Subscribe to this mod's changes

synthesis-checkpoint is a skill published in the GitHub repository synthesisengineering/synthesis-skills (18 stars, last pushed today), licensed Apache-2.0. It adds 47 tokens to every session and 3,393 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 2026-08-30.