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 charlieviettq/awesome-agent-skill --skill algo-net-centralitygit clone --depth 1 https://github.com/charlieviettq/awesome-agent-skillWrote 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/charlieviettq/awesome-agent-skill/algo-net-centrality)<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-net-centrality"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-net-centrality/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/charlieviettq/awesome-agent-skill/algo-net-centrality"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-net-centrality.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 | $0.00066 | $0.01311 |
| Opus 5 | $0.00033 | $0.00656 |
| Sonnet 5 | $0.00013 | $0.00262 |
| Haiku 4.5 | $0.00007 | $0.00131 |
Grade A, and why
"algo-net-centrality" 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 12d 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.
This is a copy
94% identical to algo-net-centrality — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Network Centrality Metrics
Overview
Centrality measures quantify node importance in a network. Four classical metrics: degree (connections), betweenness (bridge role), closeness (proximity), eigenvector (connection quality). Each captures a different aspect of importance. Complexity ranges from O(V+E) for degree to O(V×E) for betweenness.
When to Use
Trigger conditions:
- Identifying key influencers or critical nodes in social/organizational networks
- Analyzing network vulnerabilities (which node failure causes most damage)
- Comparing node importance across different dimensions
When NOT to use:
- For group/community detection (use community detection algorithms)
- For information spread modeling (use epidemic models)
Algorithm
IRON LAW: Different Centrality Metrics Answer DIFFERENT Questions
- Degree: Who has the most connections? (popularity)
- Betweenness: Who bridges communities? (brokerage)
- Closeness: Who can reach everyone fastest? (efficiency)
- Eigenvector: Who is connected to important people? (prestige)
Using the WRONG metric answers the WRONG question. Choose based on
what "important" means in your context.
Phase 1: Input Validation
Build network graph from edge list or adjacency matrix. Determine: directed vs undirected, weighted vs unweighted, connected vs disconnected. Gate: Graph is well-formed, largest connected component identified.
Phase 2: Core Algorithm
- Degree centrality: C_D(v) = deg(v) / (N-1). O(V+E).
- Betweenness centrality: C_B(v) = Σ(σ_st(v) / σ_st) for all s,t pairs. Fraction of shortest paths through v. O(V×E).
- Closeness centrality: C_C(v) = (N-1) / Σd(v,u). Inverse of average shortest path. O(V×(V+E)).
- Eigenvector centrality: Score proportional to sum of neighbors' scores. Power iteration until convergence. O(k×E).
Phase 3: Verification
Check: centrality values normalized [0,1]. Top nodes by each metric may differ — this is expected and informative. Sanity check top-5 against domain knowledge. Gate: All metrics computed, top nodes make intuitive sense.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 105 lines · 66 tokens per session scan A 358539bd98d7
"algo-net-centrality" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 1,311 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to algo-net-centrality, differing in 8 lines, and is treated as a copy.
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