New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Knowledgebase

by open-edge-platform in open-edge-platform/edge-ai-suites

Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses.

Apache-2.0Auto-check passedKnowledge Management

Install Knowledgebase

skills CLI
$ npx skills add open-edge-platform/edge-ai-suites --skill knowledgebase -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install open-edge-platform/edge-ai-suites knowledgebase --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/open-edge-platform/edge-ai-suites.git skills-src && mkdir -p .claude/skills && cp -r skills-src/metro-ai-suite/enterprise-data-intelligence/skills/knowledgebase .claude/skills/knowledgebase && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
knowledgebase
GitHub stars
140
Token cost
~900 tokens
SKILL.md length
305 words
Files
2
Skills in repo
15
Repo updated
First seen
Licence
Apache-2.0

At a glance

Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses.

  • Works in 3 steps: Use the Bash tool to execute /ecrag… → Wait for the command to complete and get… → Parse the output and present it to the…
  • : product comparisons
  • SKILL.md covers 📋 QUICK START - Do This…, 🚨 CRITICAL EXECUTION…, Core Principles and Core Tool
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Knowledgebase is an agent skill from open-edge-platform/edge-ai-suites. Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses. Use for: product comparisons, technical analysis, documentation generation, competitive analysis, benchmark reports, specification queries, or any knowledge base retrieval task.

Its SKILL.md is about 900 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in Knowledge Management, covering Knowledge bases, Competitor analysis and Retrieval-augmented generation. It works with Bash. The repository describes itself as: A curated collection of sample applications intended for reference in developing optimized AI solutions and testing hardware performance across various industry use cases. The licence is Apache-2.0.

When your agent uses it

  • : product comparisons
  • Technical analysis
  • Documentation generation
  • Competitive analysis

Example prompts

  • “/knowledgebase”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Use the Bash tool to execute /ecrag query "your question"
  2. Wait for the command to complete and get the output
  3. Parse the output and present it to the user

What it can do on your machine

Read from SKILL.md and the folder at commit 6e2ba00. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Knowledgebase loads about 900 tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 305 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~900

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from open-edge-platform/edge-ai-suites at commit 6e2ba00, republished under its Apache-2.0 licence (© open-edge-platform). 305 words, ~900 tokens.

Download SKILL.mdSave it as .claude/skills/knowledgebase/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
knowledgebase
description
Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses. Use for: product comparisons, technical analysis, documentation generation, competitive analysis, benchmark reports, specification queries, or any knowledge base retrieval task.
trigger
When user needs to retrieve any information for any purpose.
user-invocable
true
allow-model-invocation
true
priority
high

Knowledge Base - Generic ECRAG Information Retrieval & Report Generation

Use this skill when the user wants to retrieve information from the local knowledge base and generate structured outputs (reports, summaries, comparisons, documentation).

📋 QUICK START - Do This Immediately

When user asks a question, execute the curl-based ecrag wrapper via Bash:

javascript
Bash({
  command: '<SKILL_DIR>/ecrag query "user\'s question here"',
  description: "Query knowledge base"
})

Then parse the output and present it to the user. That's it!

Example: User asks "What is Intel Core Ultra 358H?"

Your immediate action:

javascript
Bash({
  command: '<SKILL_DIR>/ecrag query "What is Intel Core Ultra 358H?"',
  description: "Query KB for Intel Core Ultra 358H"
})
// Wait for output, then present results to user

🚨 CRITICAL EXECUTION REQUIREMENT 🚨

YOU MUST EXECUTE COMMANDS USING THE BASH TOOL - DO NOT JUST DESCRIBE THEM!

To query the knowledge base, you MUST:

  1. Use the Bash tool to execute <SKILL_DIR>/ecrag query "your question"
  2. Wait for the command to complete and get the output
  3. Parse the output and present it to the user

Example Bash tool call:

Bash(
  command: '<SKILL_DIR>/ecrag query "What is Intel Core Ultra 358H?"',
  description: "Query knowledge base for Intel Core Ultra 358H specifications"
)

Core Principles

⚠️ ALWAYS use Bash tool to execute <SKILL_DIR>/ecrag commands ⚠️ ⚠️ Primary information source is <SKILL_DIR>/ecrag output via Bash tool ⚠️ ⚠️ Wait for Bash execution to complete before proceeding ⚠️ ⚠️ Monitor long-running commands with session ID until completed ⚠️

The main session can handle simple queries directly. For complex tasks, launch sub-agents.

Core Tool

curl-based ecrag Wrapper (Execute via Bash Tool)

Located at <SKILL_DIR>/ecrag, this shell script calls the ECRAG HTTP API directly with curl. It does not require Python, a virtual environment, the ecrag CLI package, or jq.

CRITICAL: You MUST use the Bash tool to execute these commands!

Usage via Bash Tool
javascript
// Simple query (uses 'rag' mode by default)
Bash({
  command: '<SKILL_DIR>/ecrag query "your question here"',
  description: "Query knowledge base"
})

Optional query settings:

bash
<SKILL_DIR>/ecrag query "your question" --mode rag --top-n 5 --max-tokens 512

Modes:

  • rag (default): full retrieval and generation through POST /v1/chatqna on the mega service
  • retrieve: context retrieval only through POST /v1/retrieval
  • mega: alias for the full ChatQnA request

Connection settings are configured with environment variables:

bash
export ECRAG_HOST="http://localhost"
export ECRAG_PORT="16010"
export ECRAG_MEGA_PORT="16011"
export ECRAG_CONNECT_TIMEOUT="10"

[!IMPORTANT]

  • curl must be available in PATH
  • ALWAYS use Bash tool to execute commands
  • Script execution takes time - wait for output
  • For long-running commands, check status with session ID
  • Never skip execution - always run the command!

© open-edge-platform, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in metro-ai-suite/enterprise-data-intelligence/skills/knowledgebase of open-edge-platform/edge-ai-suites.

  • SKILL.md
  • ecrag

Open the folder on GitHubat commit 6e2ba00

Compare with similar skills

Knowledgebase next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Knowledgebase compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Knowledgebase this skillopen-edge-platform/edge-ai-suites140—~900Automated safety check: PassApache-2.0
Openloomimelandlabs/openloomi1k—~835Automated safety check: PassApache-2.0
Clarity Gatemajiayu000/claude-skill-registry6664 repos~6.2kAutomated safety check: PassCC-BY-4.0
AutoRAG LibrarianMarker-Inc-Korea/AutoRAG5.1k—~2kAutomated safety check: PassMIT
LLM Wikipraneybehl/llm-wiki-plugin117—~5.7kAutomated safety check: PassMIT
Obsidian Wiki QueryAgriciDaniel/claude-obsidian15k—~1.2kAutomated safety check: PassMIT

Similar skills

  • Openloomi

    melandlabs/openloomi

    OpenLoomi entrypoint for skill-only agent runtimes without a plugin mechanism.

    1k GitHub stars~835 tokensUpdated 13 days ago
    Knowledge ManagementAuto-check passed

  • Clarity Gate

    majiayu000/claude-skill-registry

    Pre-ingestion verification for epistemic quality in RAG systems.

    666 GitHub starsUsed in 4 repos~6.2k tokens
    Knowledge ManagementAuto-check passed

  • AutoRAG Librarian

    Marker-Inc-Korea/AutoRAG

    Searches, summarizes, compares and answers questions from an already configured AutoRAG librarian agent over local documents and authorized datasources.

    5.1k GitHub stars~2k tokensUpdated yesterday
    Knowledge ManagementAuto-check passed

  • LLM Wiki

    praneybehl/llm-wiki-plugin

    Build and maintain an LLM-curated knowledge base from papers, articles, transcripts, notes and project findings.

    117 GitHub stars~5.7k tokensUpdated 24 days ago
    Knowledge ManagementAuto-check passed

  • Obsidian Wiki Query

    AgriciDaniel/claude-obsidian

    Answers a question strictly from a chosen Obsidian vault at quick, standard or deep depth, using a verified retrieval index when available and never changing vault files.

    15k GitHub stars~1.2k tokensUpdated 27 days ago
    Knowledge ManagementAuto-check passed

  • Vault Contextual Retrieval

    AgriciDaniel/claude-obsidian

    Builds and queries a local contextual BM25 index over an Obsidian vault, with optional Nomic reranking through Ollama and strict consent rules before any text leaves the machine.

    15k GitHub stars~1.4k tokensUpdated 27 days ago
    Knowledge ManagementAuto-check passed

More from open-edge-platform/edge-ai-suites

All 15 skills in this repo

  • Onboarding Validation

    open-edge-platform/edge-ai-suites

    Validate the get-started experience of Open Edge Platform (OEP) software components from the perspective of a first-time user.

    140 GitHub stars~3.3k tokensUpdated yesterday
    Auto-check passed

  • Sc QA

    open-edge-platform/edge-ai-suites

    Ask a natural-language question against indexed content via the Content Search RAG Q&A endpoint.

    140 GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed

  • Sc Upload

    open-edge-platform/edge-ai-suites

    Upload a file to the Content Search backend and poll the ingestion task until the file is fully indexed (status COMPLETED).

    140 GitHub stars~2.6k tokensUpdated yesterday
    Auto-check passed

  • Uav Vision Analytics

    open-edge-platform/edge-ai-suites

    Build an end-to-end UAV object detection and telemetry overlay application on Intel hardware using DL Streamer Pipeline Server with MAVLink telemetry.

    140 GitHub stars~2.6k tokensUpdated yesterday
    Auto-check: notes

  • Lvc Run App

    open-edge-platform/edge-ai-suites

    Run, start, or smoke-test the Live Video Captioning app (Docker Compose stack with dashboard on :4173).

    140 GitHub stars~796 tokensUpdated yesterday
    Auto-check passed

  • Sc Doctor

    open-edge-platform/edge-ai-suites

    Diagnose Content Search backend availability by probing the health endpoint, then surface connectivity issues between Flutter and backend when unhealthy.

    140 GitHub stars~1.4k tokensUpdated yesterday
    Auto-check: notes

Works with

Categories

Questions about Knowledgebase

What does Knowledgebase do?

Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses. Knowledgebase is an agent skill from open-edge-platform/edge-ai-suites. Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses.

When should I use Knowledgebase?

Knowledgebase fits situations like: : product comparisons; technical analysis; documentation generation; competitive analysis.

How do I install Knowledgebase in Claude Code?

Run `npx skills add open-edge-platform/edge-ai-suites --skill knowledgebase -a claude-code`. Or copy the skill folder (metro-ai-suite/enterprise-data-intelligence/skills/knowledgebase in open-edge-platform/edge-ai-suites) into .claude/skills/knowledgebase in your project. Claude Code loads it when a task matches its description.

How do I install Knowledgebase in Codex?

Run `npx skills add open-edge-platform/edge-ai-suites --skill knowledgebase -a codex`. Or copy the skill folder (metro-ai-suite/enterprise-data-intelligence/skills/knowledgebase in open-edge-platform/edge-ai-suites) into .agents/skills/knowledgebase in your project. Codex loads it when a task matches its description.

Can I use Knowledgebase in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add open-edge-platform/edge-ai-suites --skill knowledgebase -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/knowledgebase, .gemini/skills/knowledgebase, .github/skills/knowledgebase and .opencode/skills/knowledgebase in your project.

What does Knowledgebase need to run?

SKILL.md names no scripts, command-line tools or credentials: Knowledgebase is instructions for the agent only.

Does Knowledgebase access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Knowledgebase safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Knowledgebase use?

Knowledgebase is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Knowledgebase use?

About 900 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Knowledgebase?

Skills that share tags, products or a category with Knowledgebase: Openloomi (melandlabs/openloomi, 1k stars), Clarity Gate (majiayu000/claude-skill-registry, 666 stars), AutoRAG Librarian (Marker-Inc-Korea/AutoRAG, 5.1k stars) and LLM Wiki (praneybehl/llm-wiki-plugin, 117 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Knowledgebase?

open-edge-platform (a GitHub organization) maintains it in open-edge-platform/edge-ai-suites, which has 140 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 6, 2026.

Source: open-edge-platform/edge-ai-suites on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.