Borrowing it
Nothing to install: this file belongs to cunicopia-dev/knowledge-graph-rdbms. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cunicopia-dev/knowledge-graph-rdbms/main/.claude/skills/kg-compose/SKILL.mdgit clone --depth 1 https://github.com/cunicopia-dev/knowledge-graph-rdbmsWrote 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/cunicopia-dev/knowledge-graph-rdbms/kg-compose)<a href="https://agentmods.dev/skills/cunicopia-dev/knowledge-graph-rdbms/kg-compose"><img src="https://agentmods.dev/badge/skills/cunicopia-dev/knowledge-graph-rdbms/kg-compose/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.
<a href="https://agentmods.dev/skills/cunicopia-dev/knowledge-graph-rdbms/kg-compose"><img src="https://agentmods.dev/badge/skills/cunicopia-dev/knowledge-graph-rdbms/kg-compose.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00113 | $0.01615 |
| Opus 5.5 | $0.00045 | $0.00646 |
| Sonnet 5.5 | $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 2mo 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.
- 2mo 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 2mo ago), licensed MIT. It adds 113 tokens to every session and 1,615 once invoked, about $0.0005 per session on Opus 5.5. 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.
kg-compose compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| kg-composecunicopia-dev/knowledge-graph-rdbms | Skill | 1 | 2mo ago | MIT | A | 113 | Claude Code |
| embeddingsruvnet/ruflo | Skill | 81k | yesterday | MIT | A | 62 | Claude Code |
| rag-pineconedavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 65 | Claude Code, Codex |
| data-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 35 | Claude Code, Codex |
| similarity-search-patternsforyourhealth111-pixel/Vibe-Skills | Skill | 3.8k | 3d ago | Apache-2.0 | A | 30 | Claude Code, Codex |
| ingesting-into-data-lakeaws/agent-toolkit-for-aws | Skill | 3.4k | yesterday | Apache-2.0 | A | 228 | Claude Code |
| graphjin-envdosco/graphjin | Skill | 3.2k | 5d ago | Apache-2.0 | A | 61 | Claude Code, Codex |