Semantica is an open-source infrastructure layer that turns enterprise data into structured context and knowledge graphs, where ontologies define meaning and graph reasoning connects facts and decisions. It is intended for AI systems and agents that need traceable, governed, and explainable context in high-stakes domains. The catalogue add-ons provide agent workflows, hooks, and plugins for operating Semantica.
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.
npx skills add semantica-agi/semantica --skill exportgit clone --depth 1 https://github.com/semantica-agi/semanticaWrote 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.
[](https://agentmods.dev/skills/semantica-agi/semantica/export)<a href="https://agentmods.dev/skills/semantica-agi/semantica/export"><img src="https://agentmods.dev/badge/skills/semantica-agi/semantica/export.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.00357 |
| Opus 5 | $0.00015 | $0.00179 |
| Sonnet 5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
export 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 9d 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.
What it actually says
/semantica:export
Export knowledge graph data. Usage: /semantica:export <format> [args]
$ARGUMENTS = format + optional target or destination.
json [--output <path>] [--filter <query>]
Export graph data as JSON.
from semantica.export.methods import export_json
export_json(data=graph_data, file_path=output, format='json')
Output: JSON file or inline JSON payload.
rdf [--format turtle|rdfxml|jsonld|ntriples|n3] [--output <path>]
Export the graph in RDF serialization.
from semantica.export.methods import export_rdf
export_rdf(data=graph_data, file_path=output, format='turtle')
Return: RDF text or file path.
parquet [--output <path>]
Export nodes and edges to Parquet for analytics.
from semantica.export.methods import export_parquet
export_parquet(data=graph_data, file_path=output, compression='snappy')
Output: Parquet dataset ready for downstream processing.
graphml|gexf|dot [--output <path>]
Export the graph to a supported graph format.
from semantica.export import GraphExporter
exporter = GraphExporter(format='graphml', include_attributes=True)
exporter.export(graph_data, output)
Output: Graph format file suitable for visualization tools.
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.
- 9d ago First seen · 68 lines · 29 tokens per session scan A 59d33407fe73
export is a skill published in the GitHub repository semantica-agi/semantica (12,329 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 357 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 2026-08-30.
Other skills, from other repositories
ai-instruction-detox
A review and cleanup method for instructions stored in files such as CLAUDE.md, AGENTS.md, skills, context, and memory.
compile
Compile a deterministic CIGAR context bundle for the current task with an explicit token budget and inspectable manifest.
effect
Prepare, inspect, commit, and reconcile governed CIGAR effects while preserving explicit authorization and idempotency.
why
Explain the provenance, authority, expiry, degradation state, and token accounting of CIGAR context already presented in this session.
checkpoint
Create an inspectable CIGAR checkpoint before compaction, interruption, or a meaningful task boundary.
handoff
Create or accept a recipient-specific CIGAR handoff without forwarding the parent conversation transcript.