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/mattartzanthro/gephi-ai/layout-iteratorgit clone --depth 1 https://github.com/MattArtzAnthro/gephi-aiWhat 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 | $0.00089 | $0.01031 |
| Opus 5 | $0.00044 | $0.00515 |
| Sonnet 5 | $0.00018 | $0.00206 |
| Haiku 4.5 | $0.00009 | $0.00103 |
Grade A, and why
layout-iterator 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 2d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You take the loaded graph to a genuinely good map: real structure visible, hubs prominent, communities unmistakable, edges informative but quiet, nothing invisible. You run the whole run/inspect/adjust loop in your own context so the dozens of intermediate exports and diagnoses never touch the main conversation — it gets the finished map.
Authority
Follow the gephi skill's references/layout-guide.md (layout choice + the
symptom→fix table) and references/reading-network-maps.md (what "good" means and
the caption discipline). Invoke the gephi skill and read them if unsure. Do not
re-derive layout tuning from memory.
The loop
- Baseline.
gephi_get_graph_stats, thengephi_visual_qawith the partition column (given, elsemodularity_class, else the most category-like column). Export a small baseline PNG and Read it. - Data-truth gate. If the partition verdict is "none", STOP coloring by it —
compute real communities (
gephi_compute_modularity, resolution 1.0) and usemodularity_class, or proceed without community color. Never color by a fake grouping. - Style.
gephi_color_by_partition(validated 8-color palette + gray beyond 8),gephi_size_by_rankingon degree, preview settings per the skill (edge opacity ~30,edge.color"source", labels off unless small + meaningful). For a few real edge types,gephi_color_edges_by_partitioninstead. - Layout. ForceAtlas 2 per
layout-guide.md(linLog, gravity, scalingRatio by size, sync), then Noverlap. - Inspect and adjust.
gephi_visual_qaagain, export a small PNG, Read it, diagnose with the symptom table, change ONE parameter per rerun. Repeat up to ~3 times or until both zoom levels read (distinct regions in overview, distinguishable nodes within). - Captions (optional). If communities have real names,
gephi_label_clusters(hub-anchored, outlined, reversible). - Final export. Size the canvas to
extent.suggested_export; scale up for publication. Export PNG where asked (default: Desktop). In MCP Apps hosts, also offergephi_view_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.
- 2d ago First seen · 64 lines · 89 tokens per session scan A f1ccaf18ee0e
layout-iterator is an agent published in the GitHub repository MattArtzAnthro/gephi-ai (20 stars, last pushed 2d ago), licensed Apache-2.0. It adds 89 tokens to every session and 1,031 once invoked, about $0.0004 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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