tutorial

An interactive, learn-by-doing walkthrough for new users of a personal knowledge vault, such as a collection of connected notes. It offers researcher, manager, and personal learning tracks and saves progress between steps.

In plain words
What is it for?
Use it to start or continue a tutorial, choose a learning track, create sample notes, and understand the vault's workflow through a sequence of practical exercises.
Why use it?
It gives beginners a guided way to learn the system while creating real content. It also adapts its wording to the vault's configured terms and can resume an unfinished walkthrough.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/agenticnotetaking/arscontexta/tutorial
Any agent
npx skills add agenticnotetaking/arscontexta --skill tutorial
Clone the repo
git clone --depth 1 https://github.com/agenticnotetaking/arscontexta

Made for: Claude Code, Codex.

Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,358 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00055 $0.04358
Opus 5 $0.00028 $0.02179
Sonnet 5 $0.00011 $0.00872
Haiku 4.5 $0.00006 $0.00436

Measured yesterday against content hash c52a82af362a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tutorial 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.

skills/tutorial/SKILL.md · 497 lines

How it starts

The opening of the file, as written. The whole thing — 497 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Runtime Configuration (Step 0 — before any processing)

Read these files to configure domain-specific behavior:

  1. ops/derivation-manifest.md — vocabulary mapping, platform hints

    • Use vocabulary.notes for the notes folder name
    • Use vocabulary.note / vocabulary.note_plural for note type references
    • Use vocabulary.reduce for the extraction verb
    • Use vocabulary.reflect for the connection-finding verb
    • Use vocabulary.topic_map for MOC references
    • Use vocabulary.inbox for the inbox folder name
  2. ops/config.yaml — processing depth, domain context

If these files don't exist, use universal defaults.

EXECUTE NOW

Target: $ARGUMENTS

  • If ops/tutorial-state.yaml exists and current_step <= 5: resume from saved step
  • If target is "reset": delete ops/tutorial-state.yaml and start fresh
  • If no state file exists: begin new tutorial with track selection

START NOW. Reference below defines the flow.


Resume Detection

Read ops/tutorial-state.yaml. If it exists and tutorial is incomplete, display:

--=={ ars contexta : tutorial }==--

  Welcome back.
  Track: [track]     [step-progress] Step [N] of 5
  Resuming where you left off...

Skip to the saved current_step. Do NOT re-ask for track. If current_step > 5, tutorial is complete — offer to reset.

Progress indicator format:

  • Step 1 of 5: [=> ]
  • Step 2 of 5: [==> ]
  • Step 3 of 5: [===> ]
  • Step 4 of 5: [====> ]
  • Step 5 of 5: [=====>]

Track Selection (new tutorial only)

Display header, then use AskUserQuestion:

--=={ ars contexta : tutorial }==--

Which track fits your work best?

  (a) Researcher -- academic papers, domain
      research, literature processing

  (b) Manager -- meeting notes, strategy docs,
      decision tracking

  (c) Personal -- daily observations, goal
      setting, reflective journaling

Wait for response. Map a/b/c to researcher/manager/personal.

Write initial state to ops/tutorial-state.yaml:

track: [researcher|manager|personal]
current_step: 1
completed_steps: []
started: [ISO 8601 UTC]
last_activity: [ISO 8601 UTC]

Read the full file on GitHub · 497 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. yesterday First seen · 497 lines · 55 tokens per session scan A c52a82af362a

Subscribe to this mod's changes

tutorial is a skill published in the GitHub repository agenticnotetaking/arscontexta (3,483 stars, last pushed 6mo ago), licensed MIT. It adds 55 tokens to every session and 4,358 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.

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