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 agents/ethanolivertroy/my-agent-stuff/delegategit clone --depth 1 https://github.com/ethanolivertroy/my-agent-stuffWhat 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 | $0.00015 | $0.00164 |
| Opus 5 | $0.00008 | $0.00082 |
| Sonnet 5 | $0.00003 | $0.00033 |
| Haiku 4.5 | $0.00002 | $0.00016 |
Grade A, and why
delegate 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 2d 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
You are a delegated agent. Execute the assigned task using the provided tools. Be direct, efficient, and keep the response focused on the requested work.
If runtime bridge instructions identify a safe supervisor target and you are blocked or need a decision, use contact_supervisor with reason: "need_decision" and stay alive for the reply. Use reason: "progress_update" only for meaningful progress or unexpected discoveries that change the plan. Do not send routine completion handoffs; return normally when no coordination is needed.
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.
- 2d ago First seen · 13 lines · 15 tokens per session scan A 166a61cc5083
delegate is an agent published in the GitHub repository ethanolivertroy/my-agent-stuff (11 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 164 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 2026-08-30.
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事後分析代理 —— 分析盲測比較結果以理解為什麼贏家勝出，並生成改進建議。 也用於分析基準測試結果，發現彙總指標可能隱藏的模式和異常。 使用範例： "分析為什麼版本 A 的技能比版本 B 更好" "審查基準測試結果並找出模式" "分析測試執行結果並生成改進建議".
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盲測比較代理 —— 在不知道哪個技能產生哪個輸出的情況下比較兩個輸出。 純粹根據輸出品質和任務完成度進行判斷。 使用範例： "比較兩個版本的技能輸出" "盲測評估哪個輸出更好".
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評分代理 —— 根據執行記錄和輸出評估期望值。 同時批判評估本身的品質，識別薄弱或遺漏的斷言。 使用範例： "評估技能執行是否符合預期" "對測試結果進行評分" "驗證輸出是否滿足所有斷言".
Custom Agent Foundry
Expert at designing and creating VS Code custom agents with optimal configurations.
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Use this agent when making architectural decisions for RTK — adding new filter modules, evaluating command routing changes, designing cross-cutting features (config, tracking, tee), or assessing performance impact of structural changes. Examples: designing a new filter family, evaluating TOML DSL extensions, planning…
model-compatibility
Recommendation matrix for which model to pair with each OMC/OMO agent, framed around cost vs. quality. This page exists so the recurring "어떤 모델을 어느 agent에 박아야 함?" question stops being tribal Discord knowledge.