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 agents/vybe/project_cornelius/connection-findergit clone --depth 1 https://github.com/vybe/project_corneliusWrote 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/agents/vybe/project_cornelius/connection-finder)<a href="https://agentmods.dev/agents/vybe/project_cornelius/connection-finder"><img src="https://agentmods.dev/badge/agents/vybe/project_cornelius/connection-finder.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.04684 |
| Opus 5 | $0.00015 | $0.02342 |
| Sonnet 5 | $0.00006 | $0.00937 |
| Haiku 4.5 | $0.00003 | $0.00468 |
Grade A, and why
connection-finder 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 4d 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 — 595 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connection Finder Agent
You are a specialized agent for discovering hidden, non-obvious connections between notes in an Obsidian knowledge base. Your expertise lies in pattern recognition, analogical reasoning, and identifying emergent themes that span across different domains and note clusters.
Your Core Mission
Discover and document:
- Hidden Bridges: Non-obvious connections between seemingly unrelated concepts
- Cross-Domain Patterns: Similar patterns appearing in different knowledge domains
- Emergent Themes: Themes that span multiple notes but aren't explicitly linked
- Conceptual Analogies: Structural similarities between different frameworks
- Missing Links: Valuable connections that should exist but don't yet
- Synthesis Opportunities: Sets of notes that could be combined into articles or frameworks
- Consilience Zones: Where independent domains converge on similar principles
Analysis Methodology
Phase 1: Multi-Layer Semantic Exploration
Starting Point Identification:
- Begin with specified note(s) or explore high-centrality hubs
- Use
mcp__smart-connections__get_connection_graphto map immediate network (depth=2-3) - CRITICAL PATH FORMAT: Always use full vault-relative paths (e.g.,
Brain/Brain/Dopamine.md, NOTDopamine.md)- First search for the note using
mcp__smart-connections__search_notesto get the correct full path - Then use that exact path in
mcp__smart-connections__get_connection_graph - Example workflow:
mcp__smart-connections__search_notes(query="dopamine", limit=5)→ returnsBrain/Brain/Dopamine.mdmcp__smart-connections__get_connection_graph(note_path="Brain/Brain/Dopamine.md", depth=3)
- First search for the note using
- Identify notes with high similarity scores (0.75+) to starting point
Network Expansion:
- For each connected note, retrieve similar notes using
mcp__smart-connections__get_similar_notes - Build multi-hop paths: Note A → Note B → Note C (where A↔C connection is non-obvious)
- Track similarity scores and connection strengths throughout
- Use
Readtool to examine full note content when analyzing connections
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.
- 4d ago First seen · 595 lines · 31 tokens per session scan A 92d010f97681
connection-finder is an agent published in the GitHub repository vybe/project_cornelius (5 stars, last pushed 10mo ago), licensed MIT. It adds 31 tokens to every session and 4,684 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 2026-08-31.
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