feedback

A shortcut for reporting a bug, requesting a feature, or sending other feedback about the bengo-toolkit. It prepares a report with diagnostic details, opens it in a text editor, and opens the feedback form in a browser.

In plain words
What is it for?
Use it to create feedback reports, choose a bug, feature, or other category, review the generated Markdown draft, and open the submission form.
Why use it?
It gives you a guided way to collect the relevant information without needing a GitHub account. You review and submit the report yourself; it is not sent automatically.

Command

Install

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.

agentmods
npx agentmods add commands/llamadrive/bengo-toolkit/feedback
Clone the repo
git clone --depth 1 https://github.com/llamadrive/bengo-toolkit
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 537 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.00537
Opus 5 $0.00017 $0.00269
Sonnet 5 $0.00007 $0.00107
Haiku 4.5 $0.00003 $0.00054

Measured 2d ago against content hash 18935f1bdbca, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feedback 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.

commands/feedback.md · 27 lines

What it actually says

/report-issue のエイリアス。bengo-toolkit に対する不具合の報告・機能の要望・感想を、GitHub アカウントなしで送るための slash command。

feedback という語からこのコマンドを探す利用者が多いため、/report-issue と同じ動作をするエイリアスとして用意してある。挙動は /report-issue と完全に同一。

$ARGUMENTS の指定方法:

  • 引数なし: 対話形式で種別と本文を聞く
  • --type bug / --type feature / --type other を付けて起動すれば、その種別から開始する

動作の流れ

  1. 利用者から種別(不具合 / 機能要望 / その他)と本文を聞き取る
  2. プラグイン版・OS・実行環境などの自動診断情報を付けて、Markdown 形式の下書きを ~/.claude-bengo/reports/feedback_<日時>.md に書き出す
  3. その下書きを OS 既定のテキストエディタで開く(macOS は TextEdit、Windows はメモ帳、Linux は xdg-open)
  4. llama-drive.com のフィードバックフォームを、ブラウザで開く(種別と診断情報は URL の query param で渡してフォーム側が自動入力する)
  5. 利用者はエディタの本文を選択コピーし、フォームに貼り付けて、内容を確認してから送信する

自動送信はしない。 プラグインがネットワーク越しに送信することはない。送信はあくまで利用者の手元で、ブラウザ経由で行う。

Step 1

まず skills/report-issue/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。

Changes

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.

  1. 2d ago First seen · 27 lines · 35 tokens per session scan A 18935f1bdbca

Subscribe to this mod's changes

feedback is a command published in the GitHub repository llamadrive/bengo-toolkit (5 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 537 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 2026-08-31.