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/deepelementlab/jupyter-studio/deepnotenpx skills add deepelementlab/jupyter-studio --skill deepnotegit clone --depth 1 https://github.com/deepelementlab/jupyter-studioWrote 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/deepelementlab/jupyter-studio/deepnote)<a href="https://agentmods.dev/skills/deepelementlab/jupyter-studio/deepnote"><img src="https://agentmods.dev/badge/skills/deepelementlab/jupyter-studio/deepnote.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00025 | $0.00299 |
| Opus 5 | $0.00013 | $0.00150 |
| Sonnet 5 | $0.00005 | $0.00060 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
deepnote 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.
What it actually says
DeepNote Wiki
DeepNote is the improved llm-wiki implementation for ClawCode.
Quick Start
- Call
wiki_orientto load schema, index, and recent logs. - Call
wiki_ingestto save sources and update pages. - Call
wiki_queryto retrieve knowledge. - Call
wiki_lintregularly to prevent drift. - Use
wiki_link/wiki_historyfor maintenance and traceability.
Storage Layout
- Root path from config:
deepnote.path(default~/deepnote) - Immutable sources in
raw/ - Compiled pages in
entities/,concepts/,comparisons/,queries/ - Metadata in
.deepnote/(graph, history, index)
Improvements vs llm-wiki
- Dedicated tools instead of pure convention.
- Structured lint checks for frontmatter, links, and schema taxonomy.
- Persistent link graph and operation history.
- Hybrid retrieval path with optional vector-store backend.
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.
- 4d ago First seen · 36 lines · 25 tokens per session scan A bd3eb8119c11
deepnote is a skill published in the GitHub repository deepelementlab/jupyter-studio (53 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 25 tokens to every session and 299 once invoked, about $0.0001 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
memorix-memory
Use when prior workspace context, past decisions, solved bugs, handoff state, or durable project knowledge would help a coding task.
memorix
Use when Claude Code needs Memorix shared memory, reasoning, Git Memory, mini-skills, session handoff, orchestration coordination, or integration troubleshooting.
memorix-mini-skills
Use when durable project knowledge, gotchas, workflows, or repeated fixes should become reusable agent guidance instead of ordinary memory.
memorix-git-memory
Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.
graph
Initialize or refresh the knowledge-graph snapshot for a repository. Ensures the codebase-memory-mcp engine is present (fetching it if needed), then builds draft/graph/ and reports engine, counts, hotspots, and cycles. Accepts an optional repo path.
ai-agents-architect
Design autonomous AI agent systems. Multi-agent orchestration, tool use, memory, planning, and evaluation. Use when building AI-powered automation or agent workflows.