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LLM Knowledge Bases

LLM wiki kit

First committed by rvk7895

Published in rvk7895/llm-knowledge-bases. Publisher page

35 GitHub stars

What it is

Claude Code plugin for building LLM-maintained Obsidian wikis from raw research — compile, query, lint, and evolve your personal knowledge base. Inspired by Karpathy's knowledge base workflow.
— the description by rvk7895

AutoGineer overview, from the brain’s own files

LLM Knowledge Bases is a plugin for Claude Code designed to automate the creation and maintenance of a personal knowledge base in Obsidian. By treating the LLM as a knowledge compiler, the system ingests raw materials—such as articles, papers, and transcripts—and organizes them into a structured, interlinked wiki. Users interact with the system by feeding raw data into a designated folder, while the agent handles the compilation, indexing, and health maintenance of the vault. It supports multiple query depths, ranging from quick index lookups to deep, multi-agent research pipelines, ensuring that the knowledge base evolves alongside the user's research interests.

How it works

Memory model: LLM wiki

AutoGineer overview, from the brain’s own files

The system operates by ingesting raw source documents from a raw folder. It then compiles these into an Obsidian vault containing summaries, backlinks, and indexes. Users can query the knowledge base at three levels of depth: quick, standard, or deep. The system also performs automated maintenance tasks like linting for broken links or orphans and provides tools for deep research, which involves generating outlines and deploying parallel agents to research specific topics. All outputs are saved to an output folder or integrated back into the wiki.

Folders
FolderRoleFiles
.claudeagent-config1
docsdocs2
.claude-pluginfolder1
pluginsfolder12

Requirements

Works with: Claude Code, OpenCode

Set it up

  1. This brain runs code automatically: 1 script. Review plugins/kb/setup.sh before opening the folder in Claude Code. No step below turns a hook on for you.

    • plugins/kb/setup.sh: sh plugins/kb/setup.sh
  2. Download the brain as a ZIP and unzip it where you keep your notes or project: https://mp-staging.autogineer.com/agent-brains/rvk7895/llm-knowledge-bases/download
  3. Claude Code reads CLAUDE.md from this folder automatically.

  4. cd llm-knowledge-bases && claude

  5. AutoGineer scanned these files at commit 342686f.

  6. Not scanned by AutoGineerThe author’s README also describes installing it as a Claude Code plugin marketplace. Read its install section: AutoGineer did not scan that path. https://github.com/rvk7895/llm-knowledge-bases/blob/342686f4cdf0e969872601eabbcc10466da91431/README.md#installation
  7. First committed by rvk7895. Published in rvk7895/llm-knowledge-bases. Licence: MIT License.

Usage

AutoGineer overview, from the brain’s own files

  • Initialize a new knowledge base structure
  • Compile raw research documents into an Obsidian wiki
  • Query the knowledge base for information at varying depths
  • Perform automated health checks on the wiki
  • Execute deep research on specific topics using multi-agent pipelines
“/kb compile”
The agent processes all files in the raw/ directory and updates the Obsidian wiki with new summaries and backlinks.
“/research-deep Artificial Intelligence trends”
The agent generates a research outline and launches parallel agents to conduct deep research on each item in the outline.
“/kb lint”
The agent scans the wiki for broken links, orphans, and inconsistencies, reporting them for resolution.

Documentation by rvk7895

LLM Knowledge Bases

A Claude Code plugin that turns raw research material into an LLM-maintained Obsidian wiki -- inspired by Andrej Karpathy's description of using LLMs as knowledge compilers rather than just code manipulators.

You drop source material into raw/, run a single command, and Claude handles the rest: compiling interlinked wiki articles, maintaining indexes and backlinks, answering complex questions at multiple depth levels, and continuously improving the knowledge base over time.

The LLM owns the wiki. You rarely edit it manually -- just explore in Obsidian and keep feeding it raw data.

How It Works

  1. Ingest -- Raw documents (articles, papers, repos, YouTube transcripts, images, datasets) go into raw/

  2. Compile -- Claude builds a structured Obsidian vault with summaries, backlinks, concept articles, and auto-generated indexes

  3. Query -- Three depth levels:

    • Quick -- Answers from wiki indexes and summaries alone

    • Standard -- Cross-references the full wiki, supplements with web search

    • Deep -- Multi-agent research pipeline with parallel web search agents

  4. Output -- Markdown reports, Marp slides, matplotlib charts -- saved to output/ and optionally filed back into the wiki

  5. Maintain -- Automated health checks (broken links, orphans, inconsistencies) and suggestions for new articles and connections

Prerequisites

Obsidian plugins (Dataview, Obsidian Git, etc.) are installed automatically by the setup script during /kb-init.

Installation

In Claude Code, run:

/plugin marketplace add rvk7895/llm-knowledge-bases
/plugin install kb@llm-knowledge-bases

All skills are installed as a single plugin.

Quick Start

# Initialize a new knowledge base
/kb-init

# Add sources to raw/, then compile the wiki
/kb compile

# Query the knowledge base
/kb query

# Run a health check
/kb lint

# Deep multi-agent research on a topic
/research <topic>
/research-deep

Available Skills

SkillPurpose
kb-initOne-time setup: scaffolds directories, generates config, writes project files
kbMain skill with four workflows: compile, query, lint, evolve
researchGenerate a structured research outline for a topic
research-deepLaunch parallel agents for deep research on each outline item
research-add-fieldsAdd field definitions to an existing research outline
research-add-itemsAdd research targets to an existing outline
research-reportCompile deep research results into a markdown report

Directory Structure (after /kb-init)

raw/           -- Raw source documents
wiki/          -- LLM-compiled Obsidian vault
output/        -- Query results, slides, charts, reports
kb.yaml        -- Configuration
CLAUDE.md      -- Project instructions for Claude

X/Twitter Integration (Optional)

To ingest tweets, threads, and bookmarks from X, install Smaug:

npm install -g @steipete/bird
git clone https://github.com/alexknowshtml/smaug && cd smaug && npm install
npx smaug setup  # configures X session cookies

Once configured, paste any x.com link and the kb skill will fetch and compile it automatically. Without Smaug, you can still add X content by pasting tweet text directly or using Thread Reader App for threads.

Note: Smaug uses X session cookies for read-only access to your own data. This is not officially supported by X's TOS. Practical risk for personal use is very low, but be aware.

Attribution

  • Andrej Karpathy -- Original vision for LLM-maintained knowledge bases

  • Weizhena -- Deep Research skills adapted for the research pipeline

plugins/kb/skills/kb-init/SKILL.md


name: kb-init description: "Use when setting up a new knowledge base, bootstrapping an Obsidian vault, or when user says 'init kb', 'new knowledge base', 'create kb', or 'setup vault'. Triggers on any request to initialize or scaffold a knowledge base project."

Overview

One-time (or re-runnable) setup that bootstraps a knowledge base project as an Obsidian vault with full omni-document support.

Prerequisites

Obsidian must be installed.

Plugin Setup

After confirming the vault path, run the bundled setup script via Bash tool:

# Interactive — asks user about each optional plugin
bash plugins/kb/setup.sh /path/to/vault

# Install everything
bash plugins/kb/setup.sh /path/to/vault --all

# Install specific plugins only
bash plugins/kb/setup.sh /path/to/vault --only dataview,obsidian-git

Required plugins (always installed):

  • Dataview — query wiki articles like a database

  • Obsidian Git — auto-backup vault to git

Optional plugins (user chooses interactively):

  • Kanban — track wiki tasks on boards

  • Outliner — better list editing for article drafts

  • Tag Wrangler — rename and merge tags across the wiki

  • Local Images Plus — download and store remote images locally

Browser extension (printed as manual step):

  • Web Clipper — clip web articles into raw/

The script is idempotent — safe to re-run. If Obsidian is open, tell the user to restart it.

Flow

1. Vault Setup

Ask: create a new vault or use an existing directory? If new, scaffold .obsidian/. If existing, verify it exists.

2. Source Gathering Strategy

Ask how the user wants to get raw data in:

  • Self-serve -- User drops files in raw/. Per-type guidance:

    • Web articles: Obsidian Web Clipper extension -> raw/articles/

    • Academic papers (PDF): Download to raw/papers/

    • GitHub repos: Clone/snapshot to raw/repos/

    • Local markdown/text: Copy to raw/notes/

    • Images/diagrams/posters: Place in raw/images/

    • YouTube transcripts: Transcript tool -> raw/transcripts/

    • Podcast episodes: Audio files -> raw/transcripts/

    • Slide decks (.pptx): Place in raw/articles/

    • Datasets (CSV, JSON): Place in raw/datasets/

    • Jupyter notebooks: Place in raw/repos/

    • X/Twitter posts: Via Smaug (optional) -> raw/articles/

  • Assisted -- Claude fetches via WebFetch, Bash (clone repos, download PDFs, pull transcripts, fetch YouTube subtitles)

  • Mixed -- Some of each

3. Output Format Preferences

Ask which formats the user wants: markdown (always on), Marp slides, matplotlib charts, HTML, CSV, Excalidraw, other. Use an extensible pattern so new formats can be added later.

4. Maintenance Cadence

Inform about options:

  • Daily/hourly: /loop (e.g., /loop 1d kb lint)

  • Weekly/monthly: /schedule

  • Manual: just ask anytime

5. Check Optional Dependencies

Detect and report availability of optional tools that enhance the system:

# Check each tool
which whisper 2>/dev/null && echo "whisper: available" || echo "whisper: not installed (needed for audio/video transcription)"
which ffmpeg 2>/dev/null && echo "ffmpeg: available" || echo "ffmpeg: not installed (needed for audio extraction from video)"
which yt-dlp 2>/dev/null && echo "yt-dlp: available" || echo "yt-dlp: not installed (needed for YouTube transcript fetching)"
python -c "import pptx" 2>/dev/null && echo "python-pptx: available" || echo "python-pptx: not installed (needed for slide extraction)"
python -c "import pandas" 2>/dev/null && echo "pandas: available" || echo "pandas: not installed (needed for dataset analysis)"

Report which media types are fully supported vs. which need manual input. Don't force installation — just inform.

5.5 Gather Report Preferences

Reports, wiki compilations, and query answers are written very differently depending on who the reader is, how much depth they want, and how they want code and references handled. Capture these preferences now so every report-generating skill can apply them.

Preferences live in kb.yaml under report_preferences:. Factory defaults are in plugins/kb/references/report-style-guide.md — read that file first to see the field list, defaults, and variants.

Ask the user these 5 open-ended questions (AskUserQuestion, one at a time):

  1. "Who's the primary reader for reports from this vault? (e.g., just you, your team, or external readers like a blog or paper)" → shapes the audience field.

  2. "Any style preferences — formal / plain / casual, short / long, anything else?" → shapes the register field.

  3. "When covering technical projects, what balance of depth vs breadth do you want? (fewer items with deep walkthroughs, or broad surveys with short entries)" → shapes the depth field.

  4. "How should I handle code in reports? Inline snippets, links to github, or walkthroughs with your editor open?" → shapes the code_handling field.

  5. "Anything else worth noting upfront — diagram preferences, citation strictness, or any peeves to avoid?" → appended verbatim to the notes field, plus used to tweak diagrams / citations if a clear signal appears.

For each answer:

  • Open plugins/kb/references/report-style-guide.md.

  • Pick the variant best matching the user's answer (### Default, ### Variant (formal), etc.).

  • If the user's phrasing adds a specific constraint the variant doesn't cover, weave it in.

  • Write the resulting free-text string to the corresponding field in kb.yaml.

If the user says "use defaults" / "I don't know" / skips a question — copy the ### Default variant for that field unchanged.

The three fields not asked about at init (self_containment, citations, argument_iteration) get their ### Default variants copied in unchanged. Tell the user these defaults are in place and can be updated later via /kb-preferences update <field>.

At the end of this section, briefly summarize the captured preferences back to the user and remind them:

These preferences are stored in kb.yaml under report_preferences:. Skills will propose updates after reports based on your feedback — you'll approve before anything changes. You can edit them anytime via /kb-preferences.

6. Generate kb.yaml

Write kb.yaml at project root with paths, output_formats, obsidian config, and an integrations section. Example:

project:
  name: "My Knowledge Base"
  description: "Knowledge base for [topic]"

paths:
  raw: raw/
  wiki: wiki/
  output: output/
  raw_articles: raw/articles/
  raw_papers: raw/papers/
  raw_repos: raw/repos/
  raw_notes: raw/notes/
  raw_images: raw/images/
  raw_transcripts: raw/transcripts/
  raw_datasets: raw/datasets/

source_strategy: mixed  # self-serve, assisted, or mixed

# Auto-save web pages fetched during any workflow (compile, query, evolve)
# Only saves pages that actually contributed to the output
auto_capture_web: true

output_formats:
  - markdown
  # - charts
  # - html
  # - marp

# How reports, wiki compilations, and query answers should be written.
# Populated from the 5 init questions + factory defaults in
# plugins/kb/references/report-style-guide.md. Free-text fields — skills
# read them as instructions, not parse them as keywords. Updatable via
# /kb-preferences or by hand-editing.
report_preferences:
  audience: |
    <<FILL: style-guide "audience" variant matching user's Q1 answer, tweaked with their phrasing>>
  register: |
    <<FILL: style-guide "register" variant matching user's Q2 answer>>
  depth: |
    <<FILL: style-guide "depth" variant matching user's Q3 answer>>
  code_handling: |
    <<FILL: style-guide "code_handling" variant matching user's Q4 answer>>
  diagrams: |
    <<FILL: style-guide "diagrams" default, unless Q5 signaled otherwise>>
  self_containment: |
    <<FILL: style-guide "self_containment" default>>
  citations: |
    <<FILL: style-guide "citations" default; use "external" variant if audience is publication>>
  argument_iteration: |
    <<FILL: style-guide "argument_iteration" default>>
  notes: |
    <<FILL: Q5 "anything else" answer verbatim, or leave empty if none>>

maintenance:
  manual: true
  scheduled: false

obsidian:
  vault_path: /path/to/vault
  recommended_plugins:
    - Web Clipper
    - Dataview
    - Obsidian Git

integrations:
  smaug:
    path: null  # set automatically when Smaug is installed

  # Optional tool availability (auto-detected during init)
  tools:
    whisper: false
    ffmpeg: false
    yt_dlp: false
    python_pptx: false
    pandas: false

# Entity types recognized by the system
entity_types:
  - concept
  - method
  - model
  - tool
  - benchmark
  - dataset
  - person
  - phenomenon
  - moc

# Maturity model
maturity:
  seedling_max_age_days: 30  # lint warns after this
  budding_min_words: 300
  budding_min_sources: 2
  evergreen_min_words: 800
  evergreen_min_sources: 3

# MOC auto-generation threshold
moc:
  min_articles_per_category: 5

When the user sets up Smaug (during init or later), save the install path here. The kb skill reads this to find Smaug without searching every time.

7. Scaffold Directories

Create:

  • raw/articles/, raw/papers/, raw/repos/, raw/notes/, raw/images/, raw/transcripts/, raw/datasets/

  • wiki/

  • output/

  • .meta/ — dotfolder holding index/meta files. Must start with . — Obsidian ignores all dot-prefixed files and folders the same way it ignores .obsidian/ itself, so meta files do not appear as graph nodes, search hits, or quick-switcher entries. Renaming this to meta/ or _meta/ would cause every meta file to show up as a huge hub in the graph.

  • .obsidian/ if creating a new vault

8. Initialize Meta Files

Meta files live in .meta/ (NOT wiki/). They are read/written by the kb skill but invisible to Obsidian.

.meta/_index.md:

---
title: "Wiki Index"
updated: YYYY-MM-DD
---

# Wiki Index

Master index of all wiki articles with source hashes for incremental compilation.

<!-- Categories will be added automatically as articles are compiled -->

.meta/_sources.md:

---
title: "Source Mapping"
updated: YYYY-MM-DD
---

# Source Mapping

Mapping from raw sources to wiki articles they contributed to.

| Source | Type | Wiki Articles |
|--------|------|---------------|
<!-- Entries added automatically during compile -->

.meta/_categories.md:

---
title: "Category Tree"
updated: YYYY-MM-DD
---

# Category Tree

Auto-maintained category hierarchy.

<!-- Categories created automatically as articles are compiled -->

.meta/_evolution.md:

---
title: "Evolution Log"
updated: YYYY-MM-DD
---

# Evolution Log

Append-only log of auto-evolve actions.

| Date | Trigger | Action | Articles Affected |
|------|---------|--------|-------------------|
<!-- Entries added automatically by auto-evolve -->

.meta/_preference_history.md:

---
title: "Preference Change History"
updated: YYYY-MM-DD
---

# Preference Change History

Append-only log of changes to `report_preferences` in `kb.yaml`.

| Date | Field | Trigger | Old → New |
|------|-------|---------|-----------|
<!-- Entries added by kb-preferences or reflection steps -->

.meta/_tags.md:

---
title: "Tag Vocabulary"
updated: YYYY-MM-DD
---

# Tag Vocabulary

Canonical tag vocabulary for the wiki. All article tags must come from this list. See the kb skill's Tag Hygiene section for the namespacing rules.

## domain/* — broad subject area

<!-- Populated as articles are compiled -->

## method-family/* — class of technique

<!-- Populated as articles are compiled -->

## status/* — maturity mirror

- `status/seedling`
- `status/budding`
- `status/evergreen`

## Other

- `moc` — Map of Content pages
9. Write Project Files
  • CLAUDE.md -- project instructions for future sessions

  • README.md -- repo docs with prerequisites, setup, workflows, directory structure, and attribution for research skills

10. Next Steps Guidance

Tell user what to do next: add sources, compile, and list available workflows (compile, query, lint, evolve, reflect).

Mention omni-document support: "You can add PDFs, images, videos, audio, slides, code repos, datasets, notebooks, tweets, YouTube links, or any web URL to the raw/ directory. The compile workflow will automatically detect the type and extract knowledge."

Common Mistakes

  • Do not overwrite an existing kb.yaml without confirming with the user first.

  • Do not skip the source-gathering strategy question -- it determines the entire workflow.

  • Do not create .obsidian/ inside a directory that is already an Obsidian vault.

  • Do not assume output formats -- always ask the user.

  • Do not skip creating .meta/_evolution.md -- it's needed for auto-evolve logging.

  • Do not skip creating .meta/_preference_history.md -- it's needed for the reflection loop to log preference changes.

  • Do not skip the Report Preferences section (§5.5). Without a populated report_preferences: block, downstream skills fall back to silent defaults and the user has no way to steer output style.

  • Do not paste the field stub comments (# picked from ...) as literal values into kb.yaml -- replace each stub with the actual free-text preference string from the style-guide variant.

  • Do not place meta files under wiki/. They belong in .meta/ at the vault root. Files inside wiki/ are indexed by Obsidian and will become graph nodes. The .meta/ dotfolder is the structural guarantee that meta files stay out of the graph, search, and file explorer regardless of user settings.

  • Do not rename .meta/ to meta/ or _meta/. The leading dot is load-bearing — that's what makes Obsidian skip the folder.

  • If migrating an existing vault that has meta files under wiki/ (wiki/_index.md etc.), move them to .meta/ with the same filenames as part of init or the next compile.

21 files

Advantages

  • Automates the maintenance of interlinked wiki articles and indexes, reducing manual effort. evidence: README.md
  • Supports multi-agent research pipelines for deep, parallel investigation of topics. evidence: README.md

Limitations

  • Requires Claude Code CLI and Obsidian to function. evidence: README.md
  • The LLM owns the wiki, and manual editing of articles outside of the provided workflows is discouraged. evidence: CLAUDE.md

Security

Risk level: Medium risk

This brain runs

Install scripts (1)

  • plugins/kb/setup.sh: sh plugins/kb/setup.sh · uses the network

Agent instructions that run or fetch something (44)

  • plugins/kb/skills/kb-init/SKILL.md: After confirming the vault path, run the bundled setup script via Bash tool:
  • plugins/kb/skills/kb-init/SKILL.md: The script is idempotent — safe to re-run.
  • plugins/kb/skills/kb-init/SKILL.md: python -c "import pptx" 2>/dev/null && echo "python-pptx: available" || echo "python-pptx: not installed (needed for slide extraction)"
  • plugins/kb/skills/kb-init/SKILL.md: python -c "import pandas" 2>/dev/null && echo "pandas: available" || echo "pandas: not installed (needed for dataset analysis)"
  • plugins/kb/skills/kb-init/SKILL.md: When the user sets up Smaug (during init or later), save the install path here.
  • plugins/kb/skills/kb-preferences/SKILL.md: If missing, tell the user to run `kb-init` and stop.
  • plugins/kb/skills/kb-preferences/SKILL.md: | Invocation | Mode | Action | |---|---|---| | `/kb-preferences` (bare) | interactive | Show current prefs, ask what to update | | `/kb-preferences init` | init | Re-run the 5 init questions, regenerate all fields from style-guide + user answers | | `/kb-preferences update <field>` | up …[+30 chars]
  • plugins/kb/skills/kb-preferences/SKILL.md: re-ask matching question or accept free-text | | `/kb-preferences add-note "..."` | add-note | Append the quoted string as a new line/paragraph under `notes:` | | `/kb-preferences reflect` | reflect-now | Run the reflection step against the current conversation explicitly | | `/kb-pref …[+164 chars]
  • plugins/kb/skills/kb-preferences/SKILL.md: If missing, tell user to run `/kb-preferences init` first and stop.
  • plugins/kb/skills/kb-preferences/SKILL.md: Confirm loudly: "This will replace all 9 fields with factory defaults and re-run the 5 init questions.
  • plugins/kb/skills/kb/SKILL.md: If missing, tell the user to run `kb-init` and stop.
  • plugins/kb/skills/kb/SKILL.md: Run `/kb-preferences init` to customize."
  • plugins/kb/skills/kb/SKILL.md: After a compile or query finishes writing its output, run a **lightweight reflection step** — only propose preference updates for **high-confidence signals**:
  • plugins/kb/skills/kb/SKILL.md: The user can run `/kb-preferences reflect` manually if they want a forced pass.
  • plugins/kb/skills/kb/SKILL.md: Run lightweight reflection at the end.
  • plugins/kb/skills/kb/SKILL.md: **Detection heuristic:** Run this check for each file:
  • plugins/kb/skills/kb/SKILL.md: Please provide a transcript, or install: pip install openai-whisper"
  • plugins/kb/skills/kb/SKILL.md: Try: `yt-dlp --write-auto-sub --sub-lang en --skip-download --output "/tmp/%(id)s" "<url>"` to get subtitles · uses the network
  • plugins/kb/skills/kb/SKILL.md: Try extracting with python-pptx: `python -c "from pptx import Presentation;
  • plugins/kb/skills/kb/SKILL.md: For Parquet: `python -c "import pandas as pd;
  • plugins/kb/skills/kb/SKILL.md: Run lightweight reflection at the end (after the answer is delivered;
  • plugins/kb/skills/kb/SKILL.md: Run the appropriate pipeline.
  • plugins/kb/skills/kb/SKILL.md: Run the graph health script if available:
  • plugins/kb/skills/kb/SKILL.md: python plugins/kb/scripts/graph_health.py "<vault_path>" --json --fix-suggestions
  • plugins/kb/skills/kb/SKILL.md: Run the evaluation script if available:
  • plugins/kb/skills/kb/SKILL.md: python experiments/evaluate.py "<vault_path>" --json
  • plugins/kb/skills/kb/SKILL.md: If user approves, execute the improvements
  • plugins/kb/skills/kb/SKILL.md: Re-run evaluation to measure improvement
  • plugins/kb/skills/kb/SKILL.md: Run: `npx smaug fetch <tweet_id>` then `npx smaug process`
  • plugins/kb/skills/kb/SKILL.md: **Install Smaug** (recommended) — `git clone https://github.com/alexknowshtml/smaug && cd smaug && npm install`, then `npx smaug setup` to configure X session cookies (`auth_token` + `ct0` from browser DevTools → Cookies → x.com). · uses the network
  • plugins/kb/skills/kb/SKILL.md: After setup, **save the install path to `kb.yaml`** under `integrations.smaug.path`.
  • plugins/kb/skills/kb/SKILL.md: Try to fetch transcript: `yt-dlp --write-auto-sub --sub-lang en --skip-download --output "/tmp/%(id)s" "<url>" 2>&1` · uses the network
  • plugins/kb/skills/kb/SKILL.md: If yt-dlp not installed: try `pip install yt-dlp` then retry
  • plugins/kb/skills/kb/SKILL.md: Extract video metadata: `yt-dlp --dump-json "<url>" 2>/dev/null | python -c "import sys,json; · uses the network
  • plugins/kb/skills/kb/SKILL.md: On the next `/kb compile` run (for compile-time context searches)
  • plugins/kb/skills/kb/SKILL.md: Forgetting to dispatch the auto-evolve subagent after a query -- it must always run, even if it usually exits silently
  • plugins/kb/skills/research-add-items/SKILL.md: Execute simultaneously:
  • plugins/kb/skills/research-deep/SKILL.md: Execute in batches by batch_size (need user approval to proceed to next batch after completing one)
  • plugins/kb/skills/research-deep/SKILL.md: After completing JSON output, run validation script to ensure complete field coverage:
  • plugins/kb/skills/research-deep/SKILL.md: python ~/.claude/skills/research/validate_json.py -f {fields_path} -j {output_path}
  • plugins/kb/skills/research-deep/SKILL.md: After completing JSON output, run validation script to ensure complete field coverage:
  • plugins/kb/skills/research-deep/SKILL.md: python ~/.claude/skills/research/validate_json.py -f /home/weizhena/AIcoding/aicoding-history/fields.yaml -j /home/weizhena/AIcoding/aicoding-history/results/GitHub_Copilot.json
  • plugins/kb/skills/research-report/SKILL.md: **If `kb.yaml` itself is missing:** tell the user to run `kb-init` and stop.
  • plugins/kb/skills/research-report/SKILL.md: Run `python {topic}/generate_report.py`
  • Medium risk: runs-install-script-network-variable-host (plugins/kb/setup.sh)
  • Medium risk: network-variable-host (plugins/kb/setup.sh:81)
  • Medium risk: runs-instruction-instruction-network (plugins/kb/skills/kb/SKILL.md:206)
  • Medium risk: runs-instruction-instruction-network (plugins/kb/skills/kb/SKILL.md:571)
  • Medium risk: runs-instruction-instruction-network (plugins/kb/skills/kb/SKILL.md:596)
  • Medium risk: runs-instruction-instruction-network (plugins/kb/skills/kb/SKILL.md:600)
  • Low risk: network-instructions (.claude/settings.local.json:14)
  • Low risk: scripts-present (plugins/kb/setup.sh)
  • Low risk: network-instructions (plugins/kb/skills/kb/SKILL.md:202)
  • Low risk: autonomy-phrase (plugins/kb/skills/kb/SKILL.md:402)

Attribution and licence

First committed by
GitHub avatar of rvk7895rvk7895
Publisher
Ritvik Aryan Kalra (Community)
Source
rvk7895/llm-knowledge-bases · commit 342686f
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  • ATTRIBUTION.md (written by AutoGineer)
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