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 swDomass/AI_orchestrator --skill knowledge-transfergit clone --depth 1 https://github.com/swDomass/AI_orchestratorWrote 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/swdomass/ai_orchestrator/knowledge-transfer)<a href="https://agentmods.dev/skills/swdomass/ai_orchestrator/knowledge-transfer"><img src="https://agentmods.dev/badge/skills/swdomass/ai_orchestrator/knowledge-transfer.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 | $0.00023 | $0.00395 |
| Opus 5 | $0.00012 | $0.00198 |
| Sonnet 5 | $0.00005 | $0.00079 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
knowledge-transfer 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 7d 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
System Prompt Addition
Führe einen strukturierten Cross-Domain Know-How-Transfer in 4 Phasen durch:
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Vault-Scan: Durchsuche den Vault intelligent — bevorzuge Notizen mit hoher Wissenstiefe (viele Wikilinks, technisches Vokabular, Projekttiefe).
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Know-How-Extraktion: Identifiziere EINE tiefe Expertise-Domäne. Lese ZWISCHEN DEN ZEILEN — die Person hat ihr Wissen oft nicht explizit niedergeschrieben. Schliesse aus Projekten, Methoden und Vokabular auf das spezifische Handwerkszeug dahinter.
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Cross-Domain-Transfer: Nutze WebSearch um konkrete Probleme in anderen Branchen zu finden. Sei KONKRET und SPEZIFISCH — keine generischen Aussagen. Die Verbindung soll überraschend und nicht-offensichtlich sein.
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Synthese: Entwickle die beste Idee zu einer vollständigen Obsidian-Notiz und speichere sie unter 01_Ideen//.
Optionale Themenangabe in der Queue-Zeile (Doppelpunkt-Syntax): - [ ] Know-How Transfer: Bremsquitschen #tool:knowledge-transfer - [ ] Know-How Transfer #tool:knowledge-transfer (auto-discovery)
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.
- 7d ago First seen · 36 lines · 23 tokens per session scan A a232140d12e5
knowledge-transfer is a skill published in the GitHub repository swDomass/AI_orchestrator (5 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 395 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 2026-08-31.
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