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 strikersam/autonomous-ai-agency --skill obsidian-knowledge-graphgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/strikersam/autonomous-ai-agency/obsidian-knowledge-graph)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/obsidian-knowledge-graph"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/obsidian-knowledge-graph/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/strikersam/autonomous-ai-agency/obsidian-knowledge-graph"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/obsidian-knowledge-graph.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00022 | $0.00287 |
| Opus 5 | $0.00011 | $0.00143 |
| Sonnet 5 | $0.00004 | $0.00057 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
obsidian-knowledge-graph 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.
What it actually says
Skill: Obsidian Knowledge Graph
Purpose
Implements an Obsidian-compatible knowledge graph (agents/knowledge_graph.py) with typed edges,
BFS shortest-path, connected components, and import/export.
Usage
from agents.knowledge_graph import KnowledgeGraph, KnowledgeNode, EdgeType
g = KnowledgeGraph()
g.add_node(KnowledgeNode(node_id="n1", label="Python", tags=["language"]))
g.add_node(KnowledgeNode(node_id="n2", label="FastAPI", tags=["framework"]))
g.add_edge("n1", "n2", EdgeType.SUPPORTS)
path = g.shortest_path("n1", "n2") # ["n1", "n2"]
Key Classes
- KnowledgeNode — labeled node with content, tags, confidence
- KnowledgeGraph — directed graph, typed edges, BFS, components, export
- EdgeType — REFERENCES, DEPENDS_ON, RELATES_TO, PARENT_OF, CONTRADICTS, SUPPORTS
Testing
python -m pytest tests/test_knowledge_graph.py -v
Related Issues
- Issue #232: Obsidian Knowledge Graph
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.
- 7d ago First seen · 37 lines · 22 tokens per session scan A 08a9d6770b39
obsidian-knowledge-graph is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 287 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 2026-09-03.
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