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/miguok/fable-harness/model-dispatch-rulesnpx skills add Miguok/fable-harness --skill model-dispatch-rulesgit clone --depth 1 https://github.com/Miguok/fable-harnessWrote 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/miguok/fable-harness/model-dispatch-rules)<a href="https://agentmods.dev/skills/miguok/fable-harness/model-dispatch-rules"><img src="https://agentmods.dev/badge/skills/miguok/fable-harness/model-dispatch-rules.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 | $0.00149 | $0.02032 |
| Opus 5 | $0.00075 | $0.01016 |
| Sonnet 5 | $0.00030 | $0.00406 |
| Haiku 4.5 | $0.00015 | $0.00203 |
Grade A, and why
model-dispatch-rules 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 4d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model Dispatch Rules
一句話:主迴圈是指揮官——負責分析、派工、裁決;粗活與編碼派子代理,主迴圈只收結論、風險、決策。
模型選擇以 CLAUDE.md 分工表為準(唯一正本,此處不複製表內容以免雙源漂移;反方底線例外,正本見協議 §5 floor 句);本檔規定「怎麼派」。
使用者 指示(2026-07-04):非瑣碎的程式編寫與測試撰寫一律派 sonnet 執行;主迴圈(無論當前模型多強)負責分析與 workflow 派工。瑣碎單步(改一行、看一個檔)依下方例外由主迴圈直接做——「一律」不含瑣碎單步,兩條規則不衝突。
Commander does not do bulk work
- 主對話在 Agent / Explore / Workflow 可用時,不得自己做大範圍 repo 掃描、批次讀檔、整目錄 grep。
- 觸發委派的機械判準(任一命中即派):
- 預估要 Read >10 個檔
- Grep 結果 >100 行還需要逐檔深入
- 任務形如「找出所有 X」「盤點整個 Y」→ 派 Explore(haiku)
- 要寫或改程式碼/測試 → 派 sonnet(附派工包)
- 主對話收到的應是:結論 + 風險 + 建議決策 + 關鍵 file:line——不是原始檔傾倒。
- 例外:≤3 個已知路徑的精準讀取、改一行看一檔的瑣碎單步,主迴圈直接做(委派 overhead 反而更貴)。
- 正例:「找出所有呼叫 deploy() 的地方」→ 派 Explore,收回 file:line 清單 + 一句摘要。
- 反例:主迴圈自己
Glob **/*然後 Read 30 個檔「以防萬一」——context 被灌爆,判斷品質下降。
Dispatch packet
每次委派必含 7 欄,缺任一欄=無效派工,子代理應先要求補齊而非開工:
目標 Goal:<一句話,可驗證,不是「幫我看看」>
範圍 Scope:<這次任務動什麼;一句話界定>
非目標 Non-goals:<明確不要做的事,至少 1 條(防順手改)>
允許路徑 Allowed paths:<可讀清單 + 可寫清單;寫入預設禁止,除非明列>
驗收標準 Acceptance criteria:<可機械判定:一條可重跑的指令+預期輸出。有測試就用測試(「pytest tests/x.py 全綠」);沒有就指定別的可觀察結果(「跑 X 後 Y 檔出現 Z 欄」)。不接受「能動就好」>
回報格式 Report format:<指定下方模板>
停止條件 Stop conditions:<遇到什麼立刻停:範圍外檔案、編譯錯誤、機密、需要刪東西>
唯讀搜尋類輕量派工(如 Explore):Non-goals / Allowed paths / Report format 三欄可填「預設」 (預設=不寫入任何檔案/全 repo 唯讀/本檔回報模板),但欄位本身不可缺。
Required report format
子代理回報一律用此模板(主迴圈收到缺段的回報,退回要求補齊):
結果 TLDR:<一句話>
做了什麼:<動過的檔案清單,每檔一句>
證據:<可重跑的驗證指令 + 原始輸出/量測值;沒有證據就寫「已修改、未驗證」,不得寫「應該可以」>
超出範圍發現:<看到但沒動的問題;只回報不修>
風險與未完成:<明列;真的沒有就寫「無,理由:…」,不得空白>
Escalation and downgrade
- 一次實質錯誤即升級(此門檻管「子代理交出的結果」;自己重試同一方法的門檻是 2 次,見
cognitive-rubricsskill):子代理(sonnet/haiku)改錯檔、或驗收未過卻回報完成 → 該任務交回主迴圈(當前模型)接手分析,不給第二次盲試。 - 出界即停:子代理動了 Scope 外的檔案 → 立即停止 → 先保全現狀(複製該檔到 .bak——壞狀態也是證據)→ 定位越界變更、只還原越界的那部分 → 回報「動了 X,已還原」。專案有版控時用
git diff定位;沒有就靠上一步那份 .bak 比對。警告:整檔還原(git checkout <file>、或整份蓋回備份)會把範圍內的未提交修改一起丟掉且不可復原,禁止當預設動作。 - 特殊語法檔鐵則(PowerLanguage / EasyLanguage / Pine Script / SQL migration / CI YAML):遇編譯或語法錯誤 → 收集完整錯誤訊息原文 → 升級回報,嚴禁盲目重試語法修補——每次盲試都在燒 token,且常越改越壞、動到不該動的區塊。
- 降級:推理級任務中發現剩下的是機械性批次動作(改措辭、跑格式轉換)→ 拆出來派 haiku。
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.
- 4d ago First seen · 89 lines · 149 tokens per session scan A a84bcad7d2a5
model-dispatch-rules is a skill published in the GitHub repository Miguok/fable-harness (201 stars, last pushed 8d ago), licensed MIT. It adds 149 tokens to every session and 2,032 once invoked, about $0.0007 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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