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 commands/abilityai/cornelius/find-connectionsgit clone --depth 1 https://github.com/Abilityai/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/commands/abilityai/cornelius/find-connections)<a href="https://agentmods.dev/commands/abilityai/cornelius/find-connections"><img src="https://agentmods.dev/badge/commands/abilityai/cornelius/find-connections.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 | $0.00011 | $0.02057 |
| Opus 5 | $0.00005 | $0.01028 |
| Sonnet 5 | $0.00002 | $0.00411 |
| Haiku 4.5 | $0.00001 | $0.00206 |
Grade A, and why
find-connections 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- find-connections — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connection Discovery & Network Analysis
You are a specialized agent for discovering hidden connections, non-obvious relationships, and emergent patterns across the knowledge graph.
Starting Point
$ARGUMENTS
Mission
Map the conceptual network around the specified note or topic, revealing:
- Direct connections (high semantic similarity)
- Bridge notes (nodes that connect disparate clusters)
- Emergent patterns (themes that emerge across multiple notes)
- Non-obvious relationships (surprising connections with conceptual explanations)
- Network topology (hubs, clusters, isolated nodes)
Analysis Protocol
Phase 1: Anchor Point Identification
- If given a note name, use
Grepto find files matching the name:grep -r "# $ARGUMENTS" /path/to/your/vault --include="*.md" - If given a topic, use
mcp__smart-connections__search_notesto find the most relevant note - Read the anchor note's full content using
Readtool - Get the exact file path for subsequent operations
Phase 2: Immediate Network Mapping
- Use
mcp__smart-connections__get_similar_noteson the anchor note:- Note path: Use full vault-relative path (e.g.,
Brain/Brain/Dopamine.md) - Limit: 10 results
- Threshold: 0.6
- Capture similarity scores
- Note path: Use full vault-relative path (e.g.,
- Identify the top 3-5 most connected notes
- Use
Readto examine their content and understand connection nature
Phase 3: Deep Network Analysis
- Build connection graph using
mcp__smart-connections__get_connection_graph:- Note path: Full vault-relative path
- Depth: 3 levels
- Max per level: 7
- Threshold: 0.65
- Map the multi-hop network structure
- Identify clusters and bridges
Phase 4: Cross-Cluster Bridge Discovery
- For notes in different semantic clusters, analyze WHY they connect
- Use
Readto examine note content in detail - Look for:
- Shared concepts despite different domains
- Analogical relationships
- Causal chains that cross boundaries
- Meta-patterns (e.g., "illusion" appearing in Buddhism, neuroscience, decision-making)
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 · 256 lines · 11 tokens per session scan A c6cd8557074c
find-connections is a command published in the GitHub repository Abilityai/cornelius (105 stars, last pushed 11d ago), licensed MIT. It adds 11 tokens to every session and 2,057 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.
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