fuxi-engineer

fuxi-engineer is a skill for Claude Code, Codex from OpenLinkSoftware/ai-agent-skills. It costs 32 tokens per session (2,804 once invoked), scanned A, original, MIT.

A Python reasoning toolkit for semantic-web data: structured information described with RDF, rules and vocabularies described with OWL, and queries written in SPARQL. It works with RDFLib and can reason over ontologies, which are formal descriptions of concepts and their relationships.

In plain words
What is it for?
Interpreting OWL rules, answering SPARQL queries, adding ontology annotations, proving statements, summarizing ontologies, validating OWL 2 RL files, and converting RDF formats.
Why use it?
It helps turn ontology rules into inferred facts, proofs, and query results when the needed information is not written explicitly in the data. It also supports checking and presenting ontology files.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions OpenCode.

Good fit Interpreting OWL rules, answering SPARQL queries, adding ontology annotations, proving statements, summarizing ontologies, validating OWL 2 RL files, and converting RDF formats.

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Install with agentmods
npx agentmods add skills/openlinksoftware/ai-agent-skills/fuxi-engineer
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 OpenLinkSoftware/ai-agent-skills --skill fuxi-engineer
Clone the repo
git clone --depth 1 https://github.com/OpenLinkSoftware/ai-agent-skills

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 fuxi-engineer

README.md
[![agentmods](https://agentmods.dev/badge/skills/openlinksoftware/ai-agent-skills/fuxi-engineer.svg)](https://agentmods.dev/skills/openlinksoftware/ai-agent-skills/fuxi-engineer)
Your own site
<a href="https://agentmods.dev/skills/openlinksoftware/ai-agent-skills/fuxi-engineer"><img src="https://agentmods.dev/badge/skills/openlinksoftware/ai-agent-skills/fuxi-engineer.svg" alt="Measured on agentmods" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,804 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original 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 $0.00032 $0.02804
Opus 5 $0.00016 $0.01402
Sonnet 5 $0.00006 $0.00561
Haiku 4.5 $0.00003 $0.00280

Measured 7d ago against content hash 93f54955e741, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

fuxi-engineer 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 7d 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.

fuxi-engineer/SKILL.md · 277 lines

How it starts

The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Use FuXi for semantic web reasoning (RDF, OWL, SPARQL)

FuXi is a Python bi-directional reasoning engine (forward/bottom-up + backward/top-down) companion to RDFLib.

What I do

  • Try steps of reasoning and generation of proofs
  • Add annotations to OWL ontologies
  • Summarizing an OWL ontology using InfixOWL API
  • Performing theorem proving services
  • Make use of QLever for SPARQL interlocution with ontologies and/or rules
  • Use robot to validate if an ontology is in the OWL 2 RL profile (and therefore can be used with DLP)
  • Use riot to convert between RDF formats

When to Use This Skill

  • When you need to interpret an OWL ontology rule file
  • When you need to answer SPARQL queries
  • When you need to add annotations to OWL ontology using InfixOWL API

Basic Principles

The best format for OWL ontologies is OWL/RDF/XML, for compatibility with ontology tools such as protege.
When verbalizing or serializing OWL for human eyes or reviewing narrative readability, the preferred syntax is Manchester OWL (OWL/RDF/XML):

from rdflib import Graph
from fuxi.cli.renderers import _render_man_owl as render_man_owl
from fuxi.Syntax.InfixOWL import all_classes, all_properties
ontology_graph = Graph().parse("ontology.owl")

for p in all_properties(ontology_graph):
    print(p.identifier, list(p.label))
    print(repr(p))
for c in all_classes(ontology_graph):
    print(c.__repr__(True))

Otherwise, turtle is the preferred format for RDF/XML if it has no rules or N3 if it does. SPARQL files should be managed in separate .rq files.

Some core RDF vocabularies to re-use whenever possible:

Read the full file on GitHub · 277 lines

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. 7d ago First seen · 277 lines · 32 tokens per session scan A 93f54955e741

Subscribe to this mod's changes

fuxi-engineer is a skill published in the GitHub repository OpenLinkSoftware/ai-agent-skills (38 stars, last pushed 4d ago), licensed MIT. It adds 32 tokens to every session and 2,804 once invoked, about $0.0002 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 2026-08-30.

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