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 skills/2362094903-ops/study-assistant-skills/study-mindmapnpx skills add 2362094903-ops/study-assistant-skills --skill study-mindmapgit clone --depth 1 https://github.com/2362094903-ops/study-assistant-skillsWrote 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/2362094903-ops/study-assistant-skills/study-mindmap)<a href="https://agentmods.dev/skills/2362094903-ops/study-assistant-skills/study-mindmap"><img src="https://agentmods.dev/badge/skills/2362094903-ops/study-assistant-skills/study-mindmap.svg" alt="Measured on agentmods" 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 | $0.00094 | $0.00392 |
| Opus 5 | $0.00047 | $0.00196 |
| Sonnet 5 | $0.00019 | $0.00078 |
| Haiku 4.5 | $0.00009 | $0.00039 |
Grade A, and why
study-mindmap 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 6d 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
Study Mind Map
Render the knowledge tree in knowledge.json into an interactive HTML mind map. Never hand-write the HTML.
New layout:
python3 ~/.claude/skills/study-mindmap/scripts/build_mindmap.py \
<study-dir>/internal/state/knowledge.json --chapter <N>
Output: <study-dir>/internal/mindmaps/chapter-XX.html. Legacy root knowledge.json outputs to legacy mindmaps/.
Preconditions
knowledge.json must exist and pass validate_workspace.py. This skill renders only; it does not split chapters into points.
Each leaf should be a small teachable/testable unit. A missing formula, law, graph-reading method, or definition is worse than an extra point.
Features to mention to the learner
- Click nodes to collapse/expand.
- Drag to pan, wheel to zoom.
- Search highlights matches and expands their path.
- Leaf colors: 灰 = 未学, 红 = 薄弱, 黄 = 基本, 浅绿 = 熟练, 绿 = 精通.
- High-importance points show a star.
- Hover shows id, importance, status, mastery, note.
Regenerate when
- Any point status/mastery/note changes.
- The knowledge list is revised.
Re-running overwrites the file in place. The browser tab only needs refresh.
What ships with it
2 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.
- 6d ago First seen · 41 lines · 94 tokens per session scan A 84d36d5a82b5
study-mindmap is a skill published in the GitHub repository 2362094903-ops/study-assistant-skills (18 stars, last pushed 28d ago), licensed MIT. It adds 94 tokens to every session and 392 once invoked, about $0.0005 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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