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Knowledge Graph Builder

Checked
daffy0208·vlatest·ai-ml·MIT

This tool automatically constructs knowledge graphs from text data, streamlining information organization and analysis for deeper insights.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it Knowledge Graph Builder, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add daffy0208/ai-dev-standards --skill "Knowledge Graph Builder" -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

daffy0208

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned daffy0208/ai-dev-standards at 32c3241e48.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
32c3241e48
Manifest
skills/knowledge-graph-builder/SKILL.md
Scanned
3 files, 814 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Knowledge Graph Builder skill enables AI agents to automatically construct knowledge graphs from text data. It transforms unstructured information into a structured format, representing entities and their relationships as nodes and edges respectively. This allows for enhanced reasoning capabilities, fact verification, and deeper insights compared to traditional methods like document-based search or relational databases. The tool focuses on making implicit relationships explicit within a domain.

When to use it

  • When your domain involves complex entity relationships (e.g., people, organizations, products).
  • To verify AI-generated facts against structured knowledge.
  • For semantic search and traversing relationships between data points.
  • When needing to answer queries like "how are X and Y related?".

Key capabilities

  • Ontology Design: Defines entities (nodes), relationships (edges), and properties for a specific domain.
  • Entity Types: Supports Person, Organization, Location, Product, Concept, Event, and Document entity types.
  • Relationship Types: Includes Hierarchical (IS_A, PART_OF, REPORTS_TO), Associative (WORKS_FOR, LOCATED_IN, AUTHORED_BY, RELATED_TO), and Temporal relationships (CREATED_ON, OCCURRED_BEFORE, OCCURRED_AFTER).
  • Property Definition: Allows for defining attributes for both nodes (e.g., id, name, type) and edges (e.g., type, confidence).

Example prompts

  • "Build a knowledge graph from this document describing the company Acme Corp."
  • "Create an ontology to represent relationships between people and organizations in the tech industry."
  • “What are the hierarchical relationships between different types of software?”

Tips & gotchas

  • Requires careful design of the domain's ontology (entities, relationships, properties) for optimal results.
  • Not suitable for simple tabular data or purely document-based search scenarios; relational databases and RAG with vector DB are better alternatives in those cases.
  • A team with some graph modeling expertise is beneficial to effectively utilize this skill.