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 agentmods add skills/cunicopia-dev/knowledge-graph-rdbms/kg-composenpx skills add cunicopia-dev/knowledge-graph-rdbms --skill kg-composegit clone --depth 1 https://github.com/cunicopia-dev/knowledge-graph-rdbmsWhat 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 | $0.00113 | $0.01615 |
| Opus 5 | $0.00056 | $0.00807 |
| Sonnet 5 | $0.00023 | $0.00323 |
| Haiku 4.5 | $0.00011 | $0.00161 |
Grade A, and why
kg-compose 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
kg-compose — document → ontology
Turn unstructured source material into structured, queryable graph facts in a named kgrdbms ontology. You are the extraction engine; the ontology supplies the opinion (how aggressive to be), and every write is gated and logged so a wrong call is reversible, not permanent.
The one idea
You are mechanism; the ontology is policy. Don't impose a house style — read
the target ontology's stance and honor it. A literal legal-notes ontology and
an inferential research-notes ontology get different graphs from the same
paragraph, on purpose.
Procedure
0. Resolve the target ontology
- If the user named one, use it. If not, propose a short kebab-case name from the material and confirm.
- Check whether it exists:
kg --json ontology list. If absent, create it:kg ontology create NAME --stance <literal|inferential> --description "…". If present, do not recreate it — read its existingstance/pathfrom the list output and honor them.
1. Read the ontology's opinion
From the registry entry: stance (free-text extraction guidance — see Stance
below), allowed_kinds (if non-empty, prefer those kinds; extract others but
flag that they're outside the ontology's allowlist), id_convention (default
CURIE prefix:slug). These are the guidance you compose within.
2. Decompose the source into a {nodes, edges} model
- Nodes = the things. Each:
id(a CURIE — see Id rules),kind(a TitleCase type likePerson,Company,Method),name(display string),labels(set memberships),properties(JSON facts). - Edges = the relationships. Each:
from,to,type(UPPER_SNAKE verb likeFOUNDED,MADE_WITH,REPORTS_TO), and optionalproperties(facts about the relationship itself —year,confidence,source). - Let the stance govern how far past the literal text you go.
3. Write it (bulk, gated, logged — ONE call, not N)
Write the whole {nodes, edges} model in a single bulk operation. Do not emit
dozens of individual upsert calls — use the bulk path:
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.
- 2d ago First seen · 116 lines · 113 tokens per session scan A a96dc1cc211f
kg-compose is a skill published in the GitHub repository cunicopia-dev/knowledge-graph-rdbms (1 stars, last pushed 23d ago), licensed MIT. It adds 113 tokens to every session and 1,615 once invoked, about $0.0006 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 2026-08-31.
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