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/mattartzanthro/gephi-ai/visualizegit 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 | $0.00028 | $0.00268 |
| Opus 5 | $0.00014 | $0.00134 |
| Sonnet 5 | $0.00006 | $0.00054 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
visualize 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 3d 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.
What it actually says
Visualize
Dispatch the layout-iterator agent to take the graph currently open in Gephi to a
genuinely good map: real structure visible, hubs prominent, communities unmistakable,
edges informative but quiet, nothing invisible. This lays out and styles the graph in
place; for export alone, use /export-map.
The agent runs the whole run → visual_qa → inspect → adjust loop in its own context, so the dozens of intermediate exports and diagnoses stay out of this conversation. It returns the finished export, its caption, and a short change log.
Pass the partition column from $ARGUMENTS (if given) so the agent colors by it —
after checking it is topologically real. If $ARGUMENTS is empty, the agent picks the
grouping (modularity_class, else the most category-like column, else computes
communities). When the agent returns, show the export path and caption, and relay any
data-truth notes it surfaced (a fake grouping, missing structure, disconnected
components).
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.
- 3d ago First seen · 24 lines · 0 tokens per session scan A f7b34a2a4391
visualize is a command published in the GitHub repository MattArtzAnthro/gephi-ai (20 stars, last pushed 3d ago), licensed Apache-2.0. It adds 28 tokens to every session and 268 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.
Other commands, from other repositories
README
Git workflow and quality assurance commands for the claude-skills repository.
loop
Iteratively fix issues until all resolved or max iterations reached.
OpenSpec: Apply
Implement an approved OpenSpec change and keep tasks in sync.
auto-goal
goal 래퍼 — /goal 생성, 상태 확인, 완료/blocked handoff를 goal tool 또는 slash command로 연결합니다.
dispatcher
Pick the next-best repo to work on across the portfolio — rank free repos, recommend one, claim its lease atomically, and route to the entry command.
implement-task
根据技术方案实施任务并输出实现报告.