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 karaage0703/ai-assistant-workspace --skill xs-transcribergit clone --depth 1 https://github.com/karaage0703/ai-assistant-workspaceWrote 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/karaage0703/ai-assistant-workspace/xs-transcriber)<a href="https://agentmods.dev/skills/karaage0703/ai-assistant-workspace/xs-transcriber"><img src="https://agentmods.dev/badge/skills/karaage0703/ai-assistant-workspace/xs-transcriber/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/karaage0703/ai-assistant-workspace/xs-transcriber"><img src="https://agentmods.dev/badge/skills/karaage0703/ai-assistant-workspace/xs-transcriber.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 40 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
- medium MCP Rug Pull · line 51 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
- medium Rogue Agent · line 45 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00110 | $0.01069 |
| Opus 5 | $0.00055 | $0.00535 |
| Sonnet 5 | $0.00022 | $0.00214 |
| Haiku 4.5 | $0.00011 | $0.00107 |
Grade A, and why
xs-transcriber scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
音声文字起こし
音声ファイルをテキストに変換する。
絶対遵守事項
- 長時間処理(10分以上の音声)はPID・ログ・終了コードを保存し、親process groupから分離して実行
対話フロー
Step 1: ファイル指定
「文字起こしする音声ファイルのパスを指定してください」
対応形式: mp3, wav, m4a, ogg, flac
Step 2: モデル選択
「文字起こしモデルを選択してください」
| # | モデル | 速度 | 精度 | 用途 |
|---|---|---|---|---|
| 1 | tiny | 最高速 | 最低 | テスト用 |
| 2 | base | 高速 | 標準 | 推奨 |
| 3 | small | 中速 | 中精度 | バランス |
| 4 | medium | 低速 | 高精度 | 高品質 |
| 5 | large | 最低速 | 最高 | 最高品質 |
Step 3: 実行
出力先は音声ファイルと同じディレクトリに .txt 拡張子で保存。
# 短い音声(10分以下)はフォアグラウンド
uvx transcriber_tool transcribe "[音声ファイルパス]" --model-size [モデル] --output "[出力パス].txt"
# 長い音声(10分以上)はバックグラウンド
# 以下はLinux / WSLの例。macOSではlaunchdなどservice managerを使う
TRANSCRIPTION_STATE_DIR="$(mktemp -d)"
setsid bash -lc '
state_dir="$1"
input="$2"
model="$3"
output="$4"
echo $$ > "$state_dir/pid"
uvx transcriber_tool transcribe "$input" --model-size "$model" --output "$output" > "$state_dir/transcription.log" 2>&1
rc=$?
echo "$rc" > "$state_dir/exit"
exit "$rc"
' bash "$TRANSCRIPTION_STATE_DIR" "[音声ファイルパス]" "[モデル]" "[出力パス].txt" >/dev/null 2>&1 &
sleep 2
ps -o pid,ppid,sid,pgid,stat,etime,cmd -p "$(cat "$TRANSCRIPTION_STATE_DIR/pid")"
echo "State: $TRANSCRIPTION_STATE_DIR"
Step 4: 進行状況確認(バックグラウンド実行時)
# ログ確認
tail -f "$TRANSCRIPTION_STATE_DIR/transcription.log"
# 完了確認
cat "$TRANSCRIPTION_STATE_DIR/exit"
xangiでturnを跨ぐ場合は、処理の末尾で終了状態を保存した後に xangi tool trigger を呼ぶ。triggerを設定できない環境では、ログ・終了状態の確認をユーザーへ明示的に引き継ぎ、自動で戻ると約束しない。
Step 5: 完了報告
文字起こし完了後、以下を報告:
- 出力ファイルパス
- 文字数(概算)
- 処理時間
処理時間目安
| 音声長 | tiny | base | medium | large |
|---|---|---|---|---|
| 10分 | 30秒 | 1分 | 2-3分 | 5分 |
| 30分 | 1-2分 | 2-3分 | 5-8分 | 10-15分 |
| 60分 | 2-3分 | 4-6分 | 10-15分 | 20-30分 |
トラブルシューティング
- transcriber_tool未インストール: 初回実行時に自動インストールされる
- タイムアウト:
setsidで分離し、PID・ログ・終了コードを保存する - メモリ不足: より小さいモデル(tiny/base)を使用
- 日本語の精度が低い: モデルを large にする
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.
- 11d ago First seen · 95 lines · 110 tokens per session scan A d0b714c0e772
xs-transcriber is a skill published in the GitHub repository karaage0703/ai-assistant-workspace (137 stars, last pushed 24d ago), licensed MIT. It adds 110 tokens to every session and 1,069 once invoked, about $0.0006 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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