AutoSci is an AI research platform organized around a wiki, with an agent that supports stages of scientific work such as reading, experimentation, writing, and retaining knowledge across projects. It is for people building or using AI-assisted research workflows, with Claude Code, Codex, and OpenCode adaptations available. The catalogue add-ons extend those agent-specific workflows.
Borrowing it
Nothing to install: this file belongs to skyllwt/AutoSci. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/skyllwt/AutoSci/main/.claude/skills/visualize/SKILL.mdgit clone --depth 1 https://github.com/skyllwt/AutoSciWrote 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/skyllwt/autosci/visualize)<a href="https://agentmods.dev/skills/skyllwt/autosci/visualize"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/visualize/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/skyllwt/autosci/visualize"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/visualize.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 | $0.00000 | $0.02966 |
| Opus 5.5 | $0.00000 | $0.01186 |
| Sonnet 5.5 | $0.00000 | $0.00593 |
| Haiku 4.5 | $0.00000 | $0.00297 |
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 2mo 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 — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/visualize
Generate visualization artifacts for the OmegaWiki knowledge graph. Produces Obsidian graph config (color groups by entity type) and curated Canvas views with labeled typed edges. For interactive web exploration use the SPA Graph view (
tools/serve.py, then#/graph).
Inputs
--obsidian(optional): Generate/update.obsidian/graph.jsonwith entity-type color groups--canvas(optional): Generate Obsidian Canvas (.canvas) from graph data with labeled edges--focus <node_id>(optional): Center canvas on a specific node (e.g.,methods/my-method)--depth N(optional): BFS depth for focused canvas (default: 2)--types <list>(optional): Filter nodes to these page types, comma-separated (e.g.,papers,concepts)--edge-types <list>(optional): Filter edges to these semantic types, comma-separated (e.g.,builds_on,challenges)--all(optional, default if no flags): Generate all visualization artifacts
Outputs
wiki/.obsidian/graph.json— Obsidian graph color configuration (per-entity-type color groups)wiki/.obsidian/app.json— Obsidian app settings (only if not exists)wiki/canvases/knowledge-map.canvas— Full knowledge map Canvas with labeled edgeswiki/canvases/idea-evidence.canvas— Idea-centric subgraph Canvaswiki/canvases/focus-{node-id}.canvas— Focused Canvas (when --focus is used)- Console output: Obsidian plugin recommendations and setup instructions
The standalone-HTML explorer (wiki/graph-view.html) was retired; the
SPA Graph view at app/modules/graph.js (served by tools/serve.py)
covers the same use case and lives in the same codebase as the rest of
the frontend.
Wiki Interaction
Reads
wiki/graph/edges.jsonl— typed semantic edgeswiki/graph/citations.jsonl— bibliographic paper citationswiki/*/— all entity directories for page metadata (frontmatter)config/visualize.json— color palette and visualization preferences
Writes
wiki/.obsidian/graph.json— CREATE/OVERWRITE (local-only artifact, gitignored; regenerated each run fromconfig/visualize.json)wiki/.obsidian/app.json— CREATE only (never overwrite user customizations; gitignored)wiki/canvases/*.canvas— CREATE/OVERWRITE (local-only artifact, gitignored)
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.
- 2mo ago First seen · 269 lines · 0 tokens per session scan A 69f3b346de6c
visualize is a skill published in the GitHub repository skyllwt/AutoSci (1,706 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,966 tokens. 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.
visualize compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| visualizeskyllwt/AutoSci | Skill | 1.7k | 1mo ago | MIT | A | 0 | Claude Code |
| imagegenopenai/codex | Skill | 133k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |