Atlas / Skills / agenticnotetaking / Tutorial

TutorialSAFE

skills/agenticnotetaking/tutorial

Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.0
Hosts
—
License
MIT
Stars
3,492
01

Overview

Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.

Read from source at commit 9eccf964e924OBSERVED · 2026-10-07
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: tutorial
description: Interactive walkthrough for new users. Learn by doing — each step creates real content in your vault. Three tracks (researcher, manager, personal) with a universal learning arc. Triggers on "/tutorial", "walk me through", "how do I use this".
user-invocable: true
allowed-tools: Read, Write, Edit, Grep, Glob, AskUserQuestion, Bash
context: fork
model: opus
version: "1.0"
generated_from: "arscontexta-v1.6"
---

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

---

## Step Execution Pattern

Every step follows WHY / DO / SEE. Before each step show progress bar. After each step, update `ops/tutorial-state.yaml` (append to `completed_steps`, increment `current_step`, update `last_activity`).

### Track Adaptation Reference

Each step adapts its language and examples to the track. The structure is identical; the content varies.

| Step | Researcher | Manager | Personal |
|------|-----------|---------|----------|
| Capture | Claim from a paper | Decision from a meeting | Realization from a day |
| Discover | Cross-paper connections | Decision-stakeholder links | Observation-goal patterns |
| Process | Paper extraction | Meeting note mining | Journal crystallization |
| Maintain | Stale claims, broken citations | Orphaned decisions | Disconnected reflections |
| Reflect | Research graph growth | Institutional memory | Self-knowledge patterns |

---

### Step 1: Capture — Create your first {vocabulary.note}

**WHY:**

```
--=={ ars contexta : tutorial }==--
  [=>    ] Step 1 of 5 -- Capture

  Everything starts with a thought worth keeping.
```

Adapt the philosophy to the track:

| Track | WHY Framing |
|-------|-------------|
| researcher | "Research begins when you notice something worth remembering. A claim from a paper, a pattern across studies, a question that has not been asked. The system captures these as prose-sentence titles — each title is a proposition that reads naturally when linked to other notes." |
| manager | "Good decisions start with captured observations. A pattern from a meeting, a stakeholder concern, a strategic insight. The system turns these into connected notes where each title is a complete thought — not a label like 'Q3 planning' but a claim like 'Q3 velocity depends on reducing context switching'." |
| personal | "Growth starts with noticing. A realization during a walk, a pattern in your week, a question about what matters. The system captures these as prose-sentence notes — each title is something you genuinely believe, like 'morning routines work because they reduce decision fatigue'." |

**DO:**

Use AskUserQuestion with track-adapted prompt:

| Track | Prompt |
|-------|--------|
| researcher | "Share a claim, observation, or question from your research. One sentence — something you genuinely want to remember and build on." |
| manager | "Share a decision, pattern, or insight from your work. One sentence — something worth tracking across meetings and projects." |
| personal | "Share a thought, observation, or realization. One sentence — something you genuinely want to remember." |

Transform input into a real {vocabulary.note}:
1. Convert input to prose-as-title filename (lowercase, safe characters, full sentence)
2. Create YAML frontmatter:
   ```yaml
   ---
   description: [adds context beyond the title — scope, mechanism, or implication]
   topics: ["[[index]]"]
   created: [today's date]
   ---
   ```
3. Write 2-3 sentences developing the thought
4. Add Topics footer linking to the hub {vocabulary.topic_map}
5. Write the file to `{vocabulary.notes}/`

**SEE:**

```
  Note created:
    {vocabulary.notes}/[filename].md

  Title: [the prose title]
  Description: [the description]
  Topics: [[index]]

  Notice how the title works as prose:
    "Since [[your note title]], the question
     becomes..."

  That is what makes notes linkable. The title
  IS the t
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-07 · audit v0.4.1 · source sha 9eccf964e924full audit observations/trust-audit/skill/agenticnotetaking__tutorial.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-079eccf964e924SAFEB89first audit
05

Questions

What does the Tutorial skill do?

Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.

Is Tutorial safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Tutorial access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (9eccf964e924), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.

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