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Vault Health Batch

Community
pssah4
vault-health-batch

Autonomous batch mode for Vault Health findings. Works through orphans, missing backlinks, and tags in batches without asking on every fix.

Overview

Publisherpssah4
Repositoryvault-operator
Skill namevault-health-batch
Stars
262
Forks
30
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by pssah4 on GitHub. Read the source before you install it.

Installation

Install the Vault Health Batch AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/pssah4/vault-operator/tree/main/bundled-skills/vault-health-batch
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/pssah4/vault-operator.git /tmp/vault-operator
mkdir -p .claude/skills
cp -r /tmp/vault-operator/bundled-skills/vault-health-batch .claude/skills/vault-health-batch
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vault Health Batch in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vault Health Batch on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vault Health Batch is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Vault Health Batch Mode

You work through Vault Health findings AUTONOMOUSLY in batches. Ask the user ONLY at real decision points, NOT on every single fix. All changes are reversible via the undo bar (checkpoints are created automatically).

Phase 1: TRIAGE

  1. Call vault_health_check
  2. Read the findings and group them by type
  3. Give the user a short overview (3-5 lines):
    Vault Health: X findings
    - N orphaned notes (M of them with context)
    - N missing backlinks
    - N broken links
    - N inconsistent tags
    - N weak clusters
    
    I will start with the mechanical fixes (backlinks, tags).
    For broken links and isolated orphans I will ask you.
  4. Start Phase 2 IMMEDIATELY -- do NOT wait for confirmation

Phase 2: BATCH FIX

Work through the types in this order.

2a: Missing backlinks + orphans with context (ONE TOOL CALL)

These are mechanical fixes: entities that are referenced but do not link back.

Steps:

  1. Call vault_health_check with action: "fix_backlinks"
  2. The tool fixes ALL missing backlinks in one batch (pure code, 0 LLM cost)
  3. Show the user the result: "X entities updated, Y backlinks added"

NO read_file, NO update_frontmatter, NO sub-agent. ONE tool call does everything.

2c: Inconsistent tags (AUTONOMOUS)

Tags that differ only in upper/lower case.

Steps:

  1. Pick the more frequent variant
  2. Change all occurrences of the rarer variant via update_frontmatter
  3. NO questions

2d: Broken links (USER DECISION)

Links that point to notes that do not exist.

Steps:

  1. Show ALL broken links together (not one by one)
  2. STOP -- ask the user:
    N broken links found:
    - [[Note A]] (referenced by 3 notes)
    - [[Note B]] (referenced by 1 note)
    
    Options:
    a) Create stub notes (with basic content)
    b) Remove the links
    c) Decide one by one
    d) Skip
  3. Continue only after the answer

2e: Orphaned notes WITHOUT context (USER DECISION)

Completely isolated notes without any MOC links.

Steps:

  1. Show the first 10 isolated notes
  2. STOP -- ask the user:
    N isolated notes (no MOC properties, no incoming links):
    - Note A
    - Note B
    - ...
    
    Should I use semantic_search to find and suggest matching topics?
    Or should these notes be ignored?
  3. If yes: for each note run semantic_search, suggest a topic, update_frontmatter

2f: Weak clusters (TOP 5 ONLY)

Semantically similar notes without explicit links.

Steps:

  1. Only the top 5 pairs (highest similarity)
  2. Read both notes with read_file
  3. Suggest to the user: "Should I link [[A]] and [[B]]?"
  4. Wait for confirmation

Phase 3: REFRESH + WRAP-UP

After all fixes: call vault_health_check with refresh: true. This re-extracts the graph and rebuilds the ontology so the findings reflect the current vault state (not the stale state from before the fixes).

Then give a compact summary:

Vault Health batch finished:
- X missing backlinks fixed
- Y orphan backlinks added
- Z tags unified
- N broken links: [status]
- M isolated orphans: [status]
- Findings remaining after refresh: N

All changes are reversible via the undo bar (top of the chat).

Token efficiency rules (follow STRICTLY)

  1. NO read_file for orphans when the finding data already provides the context
  2. NO semantic_search for notes that already have MOC links
  3. Work in batches of 10 fixes of the same kind
  4. After 20 iterations: give a summary and ask "Continue?"
  5. IGNORE the fix rules in the vault_health_check output -- follow THESE rules

Autonomy rules (follow STRICTLY)

AUTONOMOUS (NO questions):

  • Backlink entries (missing backlinks, orphans with context)
  • Tag unification

WITH USER DECISION (ALWAYS ask):

  • Broken links (create vs. remove)
  • Orphans without context (classify vs. ignore)
  • Weak clusters (link yes or no)
  • Creating new entities (topics, concepts)

Frequently asked questions

What does the Vault Health Batch AI skill do?

Autonomous batch mode for Vault Health findings. Works through orphans, missing backlinks, and tags in batches without asking on every fix.

Why use Vault Health Batch on TypingMind?

Because you install it once and use it with any model. Vault Health Batch is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vault Health Batch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pssah4/vault-operator/tree/main/bundled-skills/vault-health-batch. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Vault Health Batch?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vault Health Batch?

As many as you like. As long as a model supports skills, you can use Vault Health Batch with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vault Health Batch AI skill free?

Yes. It is published on GitHub by pssah4 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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