Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/llamadrive/bengo-toolkitnpx agentmods add commands/llamadrive/bengo-toolkit/lawsuit-analysisWrote 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/commands/llamadrive/bengo-toolkit/lawsuit-analysis)<a href="https://agentmods.dev/commands/llamadrive/bengo-toolkit/lawsuit-analysis"><img src="https://agentmods.dev/badge/commands/llamadrive/bengo-toolkit/lawsuit-analysis/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/commands/llamadrive/bengo-toolkit/lawsuit-analysis"><img src="https://agentmods.dev/badge/commands/llamadrive/bengo-toolkit/lawsuit-analysis.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 | $0.00024 | $0.00468 |
| Opus 5.5 | $0.00010 | $0.00187 |
| Sonnet 5.5 | $0.00005 | $0.00094 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
lawsuit-analysis 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 1mo 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
訴訟関連文書（訴状、答弁書、準備書面、証拠説明書等）を読み取り、構造化データ（タイムライン、登場人物、主張・認否・証拠）を抽出して自己完結 HTML（ダブルクリックで開け、⌘P で PDF 化できる単一ファイル）を生成する。
MCP Apps 対応環境（Claude Desktop, Cursor 等）では併せてインライン描画も行う。
監査ログは現在の案件フォルダの ./.claude-bengo/audit.jsonl に記録される。
./.claude-bengo/ がまだ無ければ、実行時に現在のフォルダへ自動作成される。
$ARGUMENTS: 文書ファイルのパスまたはディレクトリ（任意。なければ対話で確認）。
Step 0: 動作環境ガード
Bash: python3 skills/_lib/workspace.py check --require local_fs --require docx_mcp
- exit 0 → 次の Step へ進む
- exit 2 → stdout の日本語メッセージをそのままユーザーへ表示して停止
- exit 1 → stderr の error JSON をユーザーに伝えて停止
Step 1
まず skills/lawsuit-analysis/SKILL.md を Read ツールで読み込み、そこに記載された手順に従って実行する。
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.
- 1mo ago First seen · 26 lines · 24 tokens per session scan A ed7988c1ce0c
lawsuit-analysis is a command published in the GitHub repository llamadrive/bengo-toolkit (6 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 468 once invoked, about $0.0001 per session on Opus 5.5. 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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