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 s0912758806p/agentic-sop-to-work --skill verdictgit clone --depth 1 https://github.com/s0912758806p/agentic-sop-to-workWrote 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/s0912758806p/agentic-sop-to-work/verdict)<a href="https://agentmods.dev/skills/s0912758806p/agentic-sop-to-work/verdict"><img src="https://agentmods.dev/badge/skills/s0912758806p/agentic-sop-to-work/verdict/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/s0912758806p/agentic-sop-to-work/verdict"><img src="https://agentmods.dev/badge/skills/s0912758806p/agentic-sop-to-work/verdict.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 | $0.00043 | $0.00403 |
| Opus 5 | $0.00022 | $0.00201 |
| Sonnet 5 | $0.00009 | $0.00081 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
verdict scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Skill — verdict（判定，退回邊的判定來源）
圖示範流程的第 2 步。判定完全確定性：由上游 defects 導出，不由模型決定；
編排層再用 branch predicate 讀 data.verdict 決定往前或走退回邊——控制流始終在程式裡。
綁定的單一工具
python3（標準庫）。本 skill 只此一個工具。
依賴
python>= 3.8
參數化（無硬編碼）
- 輸入：
--in <draft artifact.json>；輸出：--out <verdict artifact.json>
介面
- 輸入 artifact：
draft@1（讀data.defects、data.round）。 - 輸出 artifact：
verdict@1—data{verdict: "reject"|"pass", defects, round}，透傳trace。
fail-loud 邊界
上游沒有 defects 欄位 → exit 3，不臆測判定（缺資料不得猜結論）。
執行
python3 skills/verdict/tool.py --in <$RUN/draft.json> --out <$RUN/verdict.json>
獨立重用
skills/verdict/ + lib/kit.py 可單獨抽出；只要上游給 draft@1 即可運作。
What ships with it
1 file 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.
- 3d ago First seen · 32 lines · 43 tokens per session scan A 4a08ad07c53a
verdict is a skill published in the GitHub repository s0912758806p/agentic-sop-to-work (206 stars, last pushed 3d ago), licensed MIT. It adds 43 tokens to every session and 403 once invoked, about $0.0002 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 2026-09-08.
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