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 Orkas-AI/Orkas-Awesome-AgentSkills --skill knowledge-mapgit clone --depth 1 https://github.com/Orkas-AI/Orkas-Awesome-AgentSkillsWrote 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/orkas-ai/orkas-awesome-agentskills/knowledge-map)<a href="https://agentmods.dev/skills/orkas-ai/orkas-awesome-agentskills/knowledge-map"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/knowledge-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/orkas-ai/orkas-awesome-agentskills/knowledge-map"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/knowledge-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 | $0.00002 | $0.01768 |
| Opus 5 | $0.00001 | $0.00884 |
| Sonnet 5 | $0.00000 | $0.00354 |
| Haiku 4.5 | $0.00000 | $0.00177 |
Grade A, and why
knowledge-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 10d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
knowledge-map
Guide-and-script skill for building course knowledge maps. Use it to turn a course topic, syllabus, textbook outline, notes, or teaching materials into a structured framework, key concept explanations, concept dependencies, and optional Markdown / Markmap / Mermaid / OPML / HTML outputs.
This skill is not a tutor, homework helper, practice-question generator, or long-term study planner. It organizes what a course contains and how concepts relate; it does not teach a live lesson, solve exercises, generate full quizzes, or schedule a study calendar.
When to use
Use this skill when the user asks for:
- A course knowledge framework, knowledge map, concept map, syllabus map, or mind map.
- A structured outline from a textbook table of contents, course notes, lecture slides, Markdown, DOCX, or pasted text.
- Key concepts, prerequisite relationships, course learning order, or "what should I learn first?"
- A compact framework plus deeper explanations of selected nodes.
- Exportable course maps in Markdown, Markmap, Mermaid, OPML, or an HTML report.
Do not use this skill for:
- One-off concept tutoring or Socratic explanation.
- Homework solving, answer checking, or quiz sessions.
- Creating retrieval-practice question sets.
- Full study schedules, reminders, check-ins, or weekly plans.
- Multi-course comparison in one pass. Ask the user to split by course.
- Video/audio processing. Ask the user to provide text, transcript, outline, or notes first.
How to call
-
Identify the input mode:
topic_only: the user provides only a course topic.material_first: the user provides syllabus/notes/materials but no strong topic.hybrid: the user provides both topic and materials.
-
If the request is
topic_onlyfor a broad common course, warn that the map will be AI-inferred and ask whether the user wants to continue, provide materials, or cancel. -
Ask whether the user wants a compact map, key-node explanations, or deeper node explanations when the requested depth is unclear. Default to compact map plus key-node explanations when materials are available.
What ships with it
13 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.
- assets/report-template.html 13 KB
- references/concept-dependency-taxonomy.md 9.4 KB
- references/framework-rubric.md 7.6 KB
- references/input-schema.md 7.6 KB
- references/outline-parsing-heuristics.md 8.1 KB
- references/output-schema.md 10 KB
- references/prompt-templates.md 12 KB
- references/provenance-spec.md 7.7 KB
- scripts/assemble_result.py 27 KB runs code
- scripts/parse_outline.py 22 KB runs code
- scripts/render_outputs.py 22 KB runs code
- scripts/validate_input.py 10 KB runs code
- scripts/verify_provenance.py 12 KB runs code
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.
- 10d ago First seen · 190 lines · 2 tokens per session scan A 745431bf4d01
knowledge-map is a skill published in the GitHub repository Orkas-AI/Orkas-Awesome-AgentSkills (13 stars, last pushed 2mo ago), licensed MIT. It adds 2 tokens to every session and 1,768 once invoked, about $0.0000 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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