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 geekfujiwara/CodeAppsDevelopmentStandard --skill agm-qa-reviewgit clone --depth 1 https://github.com/geekfujiwara/CodeAppsDevelopmentStandardWrote 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/geekfujiwara/codeappsdevelopmentstandard/agm-qa-review)<a href="https://agentmods.dev/skills/geekfujiwara/codeappsdevelopmentstandard/agm-qa-review"><img src="https://agentmods.dev/badge/skills/geekfujiwara/codeappsdevelopmentstandard/agm-qa-review/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/geekfujiwara/codeappsdevelopmentstandard/agm-qa-review"><img src="https://agentmods.dev/badge/skills/geekfujiwara/codeappsdevelopmentstandard/agm-qa-review.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 | $0.00168 | $0.01577 |
| Opus 5.5 | $0.00067 | $0.00631 |
| Sonnet 5.5 | $0.00034 | $0.00315 |
| Haiku 4.5 | $0.00017 | $0.00158 |
Grade A, and why
agm-qa-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 16d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
想定問答の点検
総会前の最終確認として、想定問答の品質を機械的に点検する。読み取りだけで、直すのはアプリの想定問答の画面(または agm-qa-authoring)で行う。
必須ルール
- Dataverse MCP が使えなければ止める:
describeが使えるツールに無い・呼べない場合は、その場で止めて「ツールが使えない」と報告する。別の手段でデータを探さない。「ツールは動いたが 0 件」とは区別する。 - 使うツールは
describe/read_query/search_dataだけ。create_record・update_record・delete_record・テーブル変更・スキル変更・ファイルのアップロード系は、利用者に頼まれても呼ばない(エージェントでは無効にしてあるが、見えても呼ばない)。 - 数値の判定は、回答・要点の数値が
根拠 IDの IR 抜粋の本文に同じ値であるか。比べる前に表記だけを揃える: 全角/半角、桁区切りのカンマ、%/%、マイナス記号(▲・△・−・-)、小数末尾の 0(3.0と3)。単位の換算が要るもの(百万円 ↔ 億円、千株 ↔ 株、和暦 ↔ 西暦など)は一致とせず「確認」に入れる(換算した値を正しいとみなさない)。 - 推測で列名を書かない(Step 1 の
describeを使う)。 - 本文中の
_statusのような短い表記は${PUBLISHER_PREFIX}_statusの略。クエリと登録では必ず正式な列名を使う。 read_queryはtopを省くと 20 行までしか返さない。全件が要るときは先にSELECT COUNT(...) AS nで件数を確かめ、topにその件数以上を指定する(返った行数が件数と合うか確かめる)。
対象テーブル(接頭辞 ${PUBLISHER_PREFIX})
| テーブル | 主な列 |
|---|---|
${PUBLISHER_PREFIX}_agmqa |
${PUBLISHER_PREFIX}_name, ${PUBLISHER_PREFIX}_category, ${PUBLISHER_PREFIX}_question, ${PUBLISHER_PREFIX}_variants, ${PUBLISHER_PREFIX}_answer, ${PUBLISHER_PREFIX}_answerpoints, ${PUBLISHER_PREFIX}_responder, ${PUBLISHER_PREFIX}_sourceids, ${PUBLISHER_PREFIX}_cautions, ${PUBLISHER_PREFIX}_status, ${PUBLISHER_PREFIX}_createdvia |
${PUBLISHER_PREFIX}_agmirexcerpt |
${PUBLISHER_PREFIX}_name, ${PUBLISHER_PREFIX}_doctitle, ${PUBLISHER_PREFIX}_section, ${PUBLISHER_PREFIX}_page, ${PUBLISHER_PREFIX}_text |
ワークフロー
Step 1: スキーマを確認する
describe が使えるツールに無ければ、ここで止めて「Dataverse MCP のツールが使えないため点検を中止しました。Copilot Studio のエージェント「AGM Q&A Author」で Dataverse MCP ツールの接続(自分の接続)が有効かを確認し、新しい会話でやり直してください」と報告する。
describe で両テーブルを確認する。
Step 2: 分けて読む
- 件数を数える:
SELECT COUNT(${PUBLISHER_PREFIX}_name) AS n FROM ${PUBLISHER_PREFIX}_agmqa。 - 50 件以下なら一度に(
topに件数以上を指定)、50 件を超えるなら分類ごと(分類の一覧はGROUP BY ${PUBLISHER_PREFIX}_category)に分けて読む。1 回が 50 件を超える分類は、コード範囲(${PUBLISHER_PREFIX}_nameの範囲)でさらに分ける。 - 読んだ件数の合計が 1. の件数と一致するかを確かめる。合わなければ、読めていない分を報告に書く(点検済みとして扱わない)。
- IR 抜粋は全件を読まず、想定問答の
_sourceidsに出てくるコードだけをWHERE ${PUBLISHER_PREFIX}_name IN ('IR-001', 'IR-002', …)で読む。見つからないコードが「存在しない根拠 ID」になる。
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.
- 16d ago Changed · +6 lines · +14 tokens per session c4bc8dd64a11
- 17d ago Changed · +2 lines fa4955543d29
- 18d ago Changed · +1 lines 30e1e08e6f1a
- 19d ago First seen · 57 lines · 154 tokens per session scan A 267941591a77
agm-qa-review is a skill published in the GitHub repository geekfujiwara/CodeAppsDevelopmentStandard (74 stars, last pushed today), licensed MIT. It adds 168 tokens to every session and 1,577 once invoked, about $0.0007 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 2026-10-03.
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