Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mishahanin/heading-osnpx agentmods add skills/mishahanin/heading-os/checkpointWrote 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.
[](https://agentmods.dev/skills/mishahanin/heading-os/checkpoint)<a href="https://agentmods.dev/skills/mishahanin/heading-os/checkpoint"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os/checkpoint.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 303 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.03412 |
| Opus 5 | $0.00033 | $0.01706 |
| Sonnet 5 | $0.00013 | $0.00682 |
| Haiku 4.5 | $0.00007 | $0.00341 |
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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- checkpoint — 95% identical, 30 lines differ
How it starts
The opening of the file, as written. The whole thing — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/checkpoint
Save a manual session checkpoint without running /compact or clearing context.
What this does
- Writes ONE combined handoff file to
outputs/operations/handoff-archive/ - Updates FOUR pointer files. This session's pair sits under
.latest/{session-slug}/{summary.md,prompt.md}, which the SessionStart inject hook reads. The shared pair sits at.latest/{summary.md,prompt.md}, which/nextreads as "the newest handoff in this workspace" - Does NOT run
/compact - Does NOT clear the session
- Does NOT continue implementation after writing - wait for the user to direct next action
When to use
- Soft / hard checkpoint offer fired (
Stophook surfaced the context threshold) - About to switch to an unrelated task, want resume-ready snapshot
- Mid-implementation, want to save state before risky action
- Long session approaching natural pause point
Procedure
Step 0 - Handle a switch argument first
Split $ARGUMENTS on whitespace. If the FIRST token is exactly auto, exactly
unattended, or exactly compact-at, this is a switch. It is not a checkpoint.
Anything else is a note, including a word that merely begins with one of them.
Match the whole token, never a prefix. compact-at takes the SECOND token as its
value.
Run one of these, then stop. Do not write any file.
python scripts/checkpoint-paths.py --auto on
python scripts/checkpoint-paths.py --auto off
python scripts/checkpoint-paths.py --auto status
python scripts/checkpoint-paths.py --unattended on
python scripts/checkpoint-paths.py --unattended off
python scripts/checkpoint-paths.py --unattended status
python scripts/checkpoint-paths.py --compact-at 35
python scripts/checkpoint-paths.py --compact-at off
python scripts/checkpoint-paths.py --compact-at status
Report the command output in one line. For auto on, continue to Step 1 and
write the checkpoint as well. The operator asked at a threshold and expects this
one on disk. For unattended on, stop after the report. The operator is about to
leave, so a question here defeats the switch.
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.
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.
- 7d ago First seen · 308 lines · 66 tokens per session scan A a78b51bfe5b2
checkpoint is a skill published in the GitHub repository mishahanin/heading-os (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 66 tokens to every session and 3,412 once invoked, about $0.0003 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.
Other skills, from other repositories
agentsview-usage
Search prior session history to recall how similar work was handled before. Use when you want to leverage a past approach, check prior experience on a topic, answer "how was this handled before", or cross-verify current handling against precedent from earlier sessions.
letter-hooker
Erweitert automation-self-care um Letter Hooks, Preflight-Bootloader, Dokument-Traversierungsregeln und selbstheilende Prompt-Kontext- Anreicherung für KI-Agenten und CLIs ohne native, ereignisgetriebene JSON-Lifecycle-Hooks (wie Antigravity / Gemini CLI). Nutzen, wenn ein Agent Preflight-Regeln injizieren, vor…
honcho
Configure and troubleshoot Honcho memory for Hermes.
qmd
Hybrid local search over notes, docs, and transcripts.
hive.context-preservation
Proactively extract critical values from tool results into working notes before automatic context pruning destroys them.
hive.note-taking
Maintain a free-form scratchpad of decisions, extracted values, and open questions so context pruning doesn't lose anything you still need.