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 MattArtzAnthro/gephi-ai --skill analyze-networkgit clone --depth 1 https://github.com/MattArtzAnthro/gephi-aiWrote 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/mattartzanthro/gephi-ai/analyze-network)<a href="https://agentmods.dev/skills/mattartzanthro/gephi-ai/analyze-network"><img src="https://agentmods.dev/badge/skills/mattartzanthro/gephi-ai/analyze-network/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/mattartzanthro/gephi-ai/analyze-network"><img src="https://agentmods.dev/badge/skills/mattartzanthro/gephi-ai/analyze-network.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 | $0.00051 | $0.01041 |
| Opus 5 | $0.00026 | $0.00521 |
| Sonnet 5 | $0.00010 | $0.00208 |
| Haiku 4.5 | $0.00005 | $0.00104 |
Grade A, and why
analyze-network 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 9d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comprehensive Network Analysis
Run a full structural analysis of the current graph and present a detailed report of its properties.
Read ../gephi/references/statistics-guide.md,
../gephi/references/reading-network-maps.md, and
../gephi/references/claim-verification.md as needed. These references are
authoritative for interpretation; do not substitute a remembered rule of thumb.
Tell the user what you're doing at each step — narrate briefly before each tool call (e.g., "Computing modularity...", "Running centrality analysis...").
Steps
-
Health check: Call
gephi_health_check. If it fails, tell the user to start Gephi and stop. -
The intake question (skip if already answered in this conversation): ask in one sentence what the nodes and ties are and what they want to learn. Use their vocabulary in the whole report, and treat their expectations as hypotheses the analysis will confirm or contradict.
-
Profile first: Call
gephi_profile_graph(one call — size, density, degree distribution, components, isolates, weights, modularity, clustering, flags). Open the report with a plain-language first reading that combines their description with these numbers, and let the profile decide which deeper analyses are worth running rather than running everything. -
Degree distribution: Call
gephi_compute_degree. Query nodes to understand the degree distribution — report min, max, average, and whether it is heavy-tailed (a few high-degree hubs) or even. Do NOT label it "scale-free" or "power-law": those fits are near-indistinguishable from log-normal in practice and smuggle in a universal-law claim (Jacomy 2020). Describe hub dominance as a property of this network, not a law. -
Community structure: Call
gephi_compute_modularitywith resolution 1.0. Report the modularity score and number of communities. -
Path analysis: Call
gephi_compute_avg_path_lengthto get average path length, diameter, and radius.
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.
- 9d ago First seen · 91 lines · 51 tokens per session scan A e2c38c20be8e
analyze-network is a skill published in the GitHub repository MattArtzAnthro/gephi-ai (22 stars, last pushed 7d ago), licensed Apache-2.0. It adds 51 tokens to every session and 1,041 once invoked, about $0.0003 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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