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/catcatcatstudio/cat-skills/notebooknpx skills add catcatcatstudio/cat-skills --skill notebookgit clone --depth 1 https://github.com/catcatcatstudio/cat-skillsWrote 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/catcatcatstudio/cat-skills/notebook)<a href="https://agentmods.dev/skills/catcatcatstudio/cat-skills/notebook"><img src="https://agentmods.dev/badge/skills/catcatcatstudio/cat-skills/notebook.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 5.1 | $0.00054 | $0.05788 |
| Opus 5 | $0.00027 | $0.02894 |
| Sonnet 5 | $0.00011 | $0.01158 |
| Haiku 4.5 | $0.00005 | $0.00579 |
Grade A, and why
notebook 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Notebook
Project trail system. Initialize, save, recover, migrate, and manage project notes.
Why this exists
You are stateless. Every conversation ends and your context dies. The next agent that opens this project starts from zero — re-reads code, re-discovers constraints, re-makes mistakes you already made. The human becomes a context shuttle between amnesiac agents.
Notebook makes the project remember so you don't have to. When you save a note, you're not journaling — you're leaving a breadcrumb for a future version of yourself that has no idea what happened here. Every failure you record is a loop you prevent. Every constraint you document is a dead end the next session skips. Every decision you capture is an argument that never gets re-litigated.
The index and lessons files are designed to be fast to scan — a future agent can recover full project context in seconds instead of minutes of re-exploration. This is the difference between an agent that compounds knowledge across sessions and one that starts over every time.
Save aggressively. The cost of a note you didn't need is near zero. The cost of a note you didn't write is another wasted session.
When NOT to use this skill
- No active project context (no git repo, no project root) — say so, don't create a floating notebook
- User wants to summarize or extract knowledge from content — use
/eatinstead - Notes already exist and user just wants to read them — read directly with Read tool, skip the skill
Quick Reference
Proactive save rule: Save after every significant decision, failure, or constraint discovered — without being asked. Every ~20 tool calls without a save is too long. If you would say "I should remember this," write it now.
| Command | Action |
|---|---|
/notebook |
Init (new project) or status (existing) |
/notebook save |
Sweep the WHOLE conversation and write every unsaved insight, each as its own note — never prompts, just writes |
/notebook save resolved: <desc> |
Save a note and resolve the matching lesson |
/notebook recover |
Read index + lessons + flagged notes, summarize state — up the whole chain |
/notebook migrate [path] |
Convert messy notes into notebook format |
/notebook split <dir> |
Give a sub-project its own notebook and move its notes there — proposes, you confirm |
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.
- 5d ago First seen · 474 lines · 54 tokens per session scan A ed7fc420f175
notebook is a skill published in the GitHub repository catcatcatstudio/cat-skills (3 stars, last pushed 9d ago), licensed MIT. It adds 54 tokens to every session and 5,788 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 2026-08-31.
Other skills, from other repositories
learn-from-fix
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recall
Recall prior work from past sessions — how a bug was fixed, what was decided, where a pattern lives. Use when asked 'have we done this before' or 'how did I fix X' in Elixir/Phoenix work. ccrider MCP when available, else git + solution docs.
assigns-audit
Inspect LiveView socket assigns for memory bloat — missing temporaryassigns, unused assigns, unbounded lists needing streams, memory estimates. Use when LiveView memory grows or you need to add temporaryassigns.
compound-docs
Searchable Elixir/Phoenix/Ecto solution documentation system with YAML frontmatter. Builds institutional knowledge from solved problems. Use when consulting past solutions before investigating new issues.
context-anchoring
Manage per-feature living documents that capture decisions, constraints, and reasoning across AI sessions during active development. Scoped to feature-level work — design, implementation, bugfix, refactor — not for codebase-wide assessments or product-wide specifications (those define their own document lifecycles).…
learning-harvest
Manage the operational learnings lifecycle — load prior learnings to inform current work, harvest new patterns worth preserving, and keep the document tight over time. Provides a protocol for accumulating actionable patterns from practice that complement standards and defaults. Use when a workflow session completes…