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.
npx agentmods add skills/awslabs/agentcore-samples/persistent-notesnpx skills add awslabs/agentcore-samples --skill persistent-notesgit clone --depth 1 https://github.com/awslabs/agentcore-samplesWhat 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 | $0.00032 | $0.00309 |
| Opus 5 | $0.00016 | $0.00154 |
| Sonnet 5 | $0.00006 | $0.00062 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
persistent-notes 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 yesterday.
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.
What it actually says
Persistent Notes Skill
Save notes to a local /mnt/workspace/notes.json file.
Usage
python3 persistent-notes/scripts/note_manager.py "Your note content here"
What it does
- Appends note with timestamp to
notes.json - Creates file if it doesn't exist
- Each note includes content and ISO timestamp
- Returns JSON confirmation
Example
python3 persistent-notes/scripts/note_manager.py "Deploy to production on Friday"
Output:
{
"status": "success",
"message": "Note saved to notes.json",
"note": {
"content": "Deploy to production on Friday",
"timestamp": "2026-03-19T10:30:00.123456"
}
}
Notes Storage
Notes are saved to ./notes.json in the current working directory as a JSON array:
[
{
"content": "First note",
"timestamp": "2026-03-19T10:00:00.000000"
},
{
"content": "Second note",
"timestamp": "2026-03-19T10:30:00.000000"
}
]
What ships with it
3 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.
- yesterday First seen · 57 lines · 32 tokens per session scan A 2922e9b4b402
persistent-notes is a skill published in the GitHub repository awslabs/agentcore-samples (3,320 stars, last pushed 3d ago), licensed Apache-2.0. It adds 32 tokens to every session and 309 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.
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