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 Jellypod-Inc/school-skills --skill concept-mapgit clone --depth 1 https://github.com/Jellypod-Inc/school-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/jellypod-inc/school-skills/concept-map)<a href="https://agentmods.dev/skills/jellypod-inc/school-skills/concept-map"><img src="https://agentmods.dev/badge/skills/jellypod-inc/school-skills/concept-map/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/jellypod-inc/school-skills/concept-map"><img src="https://agentmods.dev/badge/skills/jellypod-inc/school-skills/concept-map.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00205 | $0.02350 |
| Opus 5 | $0.00102 | $0.01175 |
| Sonnet 5 | $0.00041 | $0.00470 |
| Haiku 4.5 | $0.00020 | $0.00235 |
Grade A, and why
concept-map 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 12d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
concept-map
Turn a topic string or source text into a legible graph that shows structure at a glance. Default output is Mermaid syntax (renders in GitHub, Notion, Obsidian, and Claude Code with zero install) plus a PNG/SVG when a renderer is available.
When to trigger
Activate on any phrasing that asks to visualize relationships between ideas. Examples:
Student phrasings
- "mind map of the french revolution"
- "concept map for photosynthesis"
- "show me how these ideas relate"
- "visualize this chapter as a graph"
- "map my notes on cell biology"
- "I need a mind map to study for my exam"
Teacher phrasings
- "diagram of this chapter for my 7th graders"
- "prerequisite tree for calculus"
- "cause and effect map of WWI"
- "draw a taxonomy of vertebrates"
- "flowchart the scientific method"
- "timeline of the civil rights movement"
- "markmap of my unit notes"
Anti-triggers — DO NOT invoke
- "write me a summary of X" → plain prose, not a graph.
- "give me a flowchart for this React component" → code-diagramming, out of scope.
- "draw a picture of a cell" → labeled illustration, not a concept graph.
Inputs
- Topic string (required OR source) — "the French Revolution", "photosynthesis", "derivatives".
- Source text (required OR topic) — pasted chapter, notes, or article paragraphs.
- Graph type (optional) —
tree,concept-map,flow,timeline,mindmap. Inferred if omitted (see table below). - Format (optional) —
mermaid(default),dot,markmap, orall. - Grade / level (optional) — K-2, 3-5, 6-8, 9-12, college, grad. Drives node count + vocabulary.
- Max nodes (optional) — integer, default 20, hard cap 50.
- Render (optional, default true) — auto-invoke
scripts/render.pyto produce PNG/SVG.
Inferring graph type from phrasing (before asking)
Pick the graph type from the user's wording — do NOT ask unless both topic and format are absent.
| Phrasing cue | Graph type | Mermaid directive |
|---|---|---|
| "timeline of", "history of", "events leading up to", "chronology" | timeline | timeline |
| "parts of a ___", "anatomy of", "taxonomy of", "types of", "classification" | tree (hierarchical) | graph TD |
| "prerequisite tree", "what do I need before", "dependency graph" | tree (bottom-up DAG) | graph BT or DOT rankdir=BT |
| "causes of ___", "cause and effect", "what led to" | concept map with labeled edges | graph LR with edge labels |
| "how does ___ work", "process of", "steps in", "scientific method" | flow (process) | flowchart LR |
| "mind map of", "brainstorm", "everything about ___", "map my notes" | radial mindmap | mindmap |
| "concept map", "how these ideas relate", "relationships between" | Novak concept map | graph TD with labeled edges + cross-links |
| "markmap", "outline of my notes", "heading tree" | Markmap | Markdown headings |
What ships with it
8 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.
- 12d ago First seen · 167 lines · 205 tokens per session scan A a1d1f67d6b54
concept-map is a skill published in the GitHub repository Jellypod-Inc/school-skills (6 stars, last pushed 5mo ago), licensed MIT. It adds 205 tokens to every session and 2,350 once invoked, about $0.0010 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 2026-08-31.
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