semantic-web

semantic-web is a skill for Claude Code, Codex from andreibesleaga/GABBE. It costs 16 tokens per session (363 once invoked), scanned A, original, no licence file.

A guide to organising information so computers can understand relationships between concepts, using ontologies and knowledge graphs. The Semantic Web is an approach to making web data more meaningful and connected.

In plain words
What is it for?
Use it when modelling domain knowledge, linking related data, or building knowledge graphs that support structured search and reasoning.
Why use it?
It helps prevent important relationships and meanings from being lost when information is stored across separate systems.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it when modelling domain knowledge, linking related data, or building knowledge graphs that support structured search and reasoning.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/andreibesleaga/gabbe/semantic-web
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add andreibesleaga/GABBE --skill semantic-web
Clone the repo
git clone --depth 1 https://github.com/andreibesleaga/GABBE

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for semantic-web

README.md
[![agentmods](https://agentmods.dev/badge/skills/andreibesleaga/gabbe/semantic-web/github.svg)](https://agentmods.dev/skills/andreibesleaga/gabbe/semantic-web)
Your own site
<a href="https://agentmods.dev/skills/andreibesleaga/gabbe/semantic-web"><img src="https://agentmods.dev/badge/skills/andreibesleaga/gabbe/semantic-web/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for semantic-web

Your own site · 80×15
<a href="https://agentmods.dev/skills/andreibesleaga/gabbe/semantic-web"><img src="https://agentmods.dev/badge/skills/andreibesleaga/gabbe/semantic-web.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 363 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00016 $0.00363
Opus 5 $0.00008 $0.00181
Sonnet 5 $0.00003 $0.00073
Haiku 4.5 $0.00002 $0.00036

Measured 8d ago against content hash 7d858b9d33ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

semantic-web scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/skills/data/semantic-web.skill.md · 29 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 29 lines · 16 tokens per session scan A 7d858b9d33ba

Subscribe to this mod's changes

semantic-web is a skill published in the GitHub repository andreibesleaga/GABBE (22 stars, last pushed 3d ago), with no licence file. It adds 16 tokens to every session and 363 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

Related

Other skills, from other repositories

open-ontologies

AI-native ontology engineering using 50+ MCP tools backed by an in-memory Oxigraph triple store. Build, validate, query, and govern RDF/OWL ontologies with a generate-validate-iterate loop. Use when building ontologies, knowledge graphs, RDF data, SPARQL queries, BORO/4D modeling, SHACL validation, clinical…

fabio-rovai/open-ontologies · 110 tokens

spark-environment-setup

Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.

wshobson/agents · 76 tokens

spark-memory-thermal-ops

Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour training.

wshobson/agents · 59 tokens

spark-training-gotchas

Preflight and diagnose the ten known failure modes for ML training on NVIDIA DGX Spark. Use when a training run on DGX Spark fails to start, OOMs below the 128GB limit, slows down mid-run, or before any multi-hour training job on GB10.

wshobson/agents · 63 tokens

data-quality-frameworks

Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

wshobson/agents · 37 tokens

airflow-dag-patterns

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

wshobson/agents · 42 tokens