Borrowing it
Nothing to install: this file belongs to TakaGoto/rag-learning-academy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TakaGoto/rag-learning-academy/main/.claude/skills/journal/SKILL.mdgit clone --depth 1 https://github.com/TakaGoto/rag-learning-academyWrote 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/takagoto/rag-learning-academy/journal)<a href="https://agentmods.dev/skills/takagoto/rag-learning-academy/journal"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/journal/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.
<a href="https://agentmods.dev/skills/takagoto/rag-learning-academy/journal"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/journal.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00014 | $0.00503 |
| Opus 5 | $0.00007 | $0.00251 |
| Sonnet 5 | $0.00003 | $0.00101 |
| Haiku 4.5 | $0.00001 | $0.00050 |
Grade A, and why
journal 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 9d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Journal: Capture Your Thoughts
A lightweight way for learners to jot down what clicked, what confused them, or what they want to revisit. These notes feed back into the curriculum director's recommendations.
Step 1: Get the Entry
If the learner provides text with the command (e.g., /journal embeddings finally make sense — it's just coordinates in meaning space), use that directly.
If no text is provided, prompt: "What's on your mind? Could be something that clicked, something confusing, a question for later, or just a note to yourself."
Step 2: Categorize
Tag the entry with one of these categories based on content:
- insight — something that clicked or a connection they made
- confusion — something they don't understand yet
- question — something they want to explore later
- idea — a project idea or experiment they want to try
- note — general observation
Step 3: Save the Entry
Append to progress/journal.md. Create the file if it doesn't exist.
Format:
### [date] — [category]
[their entry text]
Keep their original words. Don't rewrite or polish — this is their voice, their notes.
Step 4: Brief Response
Keep it short. Respond based on the category:
- insight: Acknowledge it. "Solid mental model. That analogy will serve you well when things get more complex."
- confusion: Normalize it and offer help. "That's a common sticking point. Want me to
/explain [topic]from a different angle?" - question: Acknowledge and bookmark. "Good question. We'll hit that in [relevant module]. Or run
/explain [topic]now if you're curious." - idea: Encourage it. "That's worth trying. When you're ready,
/sandboxcan help you prototype it." - note: Just confirm. "Noted."
Don't turn this into a teaching moment unless they ask. The journal is for them, not for the system.
Suggest next steps if appropriate:
/lessonto continue learning/roadmapto check your progress/explain [topic]if a confusion entry points to a specific concept
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.
- 9d ago First seen · 55 lines · 14 tokens per session scan A 2f2c8eae20ae
journal is a skill published in the GitHub repository TakaGoto/rag-learning-academy (18 stars, last pushed 5mo ago), licensed MIT. It adds 14 tokens to every session and 503 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.
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