xs-health-advisor

xs-health-advisor is a skill for Claude Code, Codex from karaage0703/ai-assistant-workspace. It costs 86 tokens per session (2,081 once invoked), scanned A, original, MIT.

A lifestyle tracking workflow for recording meals, exercise, walking, and sauna visits, then giving estimated calorie information and weekly feedback. It is for habit awareness, not medical advice.

In plain words
What is it for?
Use it to log food, steps, walks, workouts, sauna visits, and smartwatch data, then receive rough calorie estimates and a short comment.
Why use it?
It turns scattered reports into a dated record and makes clear when numbers are estimates rather than measurements. This can help you notice everyday patterns without treating the result as a diagnosis.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to log food, steps, walks, workouts, sauna visits, and smartwatch data, then receive rough calorie estimates and a short comment.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/karaage0703/ai-assistant-workspace/xs-health-advisor
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.

Any agent
npx skills add karaage0703/ai-assistant-workspace --skill xs-health-advisor
Clone the repo
git clone --depth 1 https://github.com/karaage0703/ai-assistant-workspace

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for xs-health-advisor

README.md
[![agentmods](https://agentmods.dev/badge/skills/karaage0703/ai-assistant-workspace/xs-health-advisor/github.svg)](https://agentmods.dev/skills/karaage0703/ai-assistant-workspace/xs-health-advisor)
Your own site
<a href="https://agentmods.dev/skills/karaage0703/ai-assistant-workspace/xs-health-advisor"><img src="https://agentmods.dev/badge/skills/karaage0703/ai-assistant-workspace/xs-health-advisor/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.

agentmods 80×15 button for xs-health-advisor

Your own site · 80×15
<a href="https://agentmods.dev/skills/karaage0703/ai-assistant-workspace/xs-health-advisor"><img src="https://agentmods.dev/badge/skills/karaage0703/ai-assistant-workspace/xs-health-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,081 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00086 $0.02081
Opus 5 $0.00043 $0.01040
Sonnet 5 $0.00017 $0.00416
Haiku 4.5 $0.00009 $0.00208

Measured 12d ago against content hash c13991f65df9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

xs-health-advisor 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 12d 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.

skills/xs-health-advisor/SKILL.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ヘルスアドバイザー

食事・運動を記録し、週次でフィードバックを提供するスキル。

絶対遵守事項

  • 対話は日本語で行う
  • 医療アドバイスはしない(あくまで生活習慣の気づき)
  • 説教くさくしない。ポジティブなトーンで
  • 完璧を求めない。「昨日より少し良い」を目指す
  • 記録にない数値を断定しない。体重・BMI・消費カロリーなどは、実測値か推定値かを明示する
  • 食事・運動を記録したら、必ず memory/YYYYMMDD.md に残す

発動条件(最重要!)

以下のいずれかに該当したら 必ず自動発動 すること:

食事の報告:

  • 「朝ごはん」「昼ごはん」「晩ごはん」「夜ごはん」「お昼」「ランチ」「ディナー」等の食事ワード
  • 「〇〇食べた」「〇〇食べました」等の食事報告
  • 食事の写真(料理・弁当・お菓子・飲み物など)
  • 具体的な食品名

運動の報告:

  • 「散歩」「ウォーキング」「歩いた」「走った」「筋トレ」等の運動ワード
  • 「サウナ」「ととのい」「銭湯」「温泉」等のサウナ・入浴ワード
  • スマートウォッチのスクリーンショット
  • サウナ記録アプリのスクリーンショット
  • 「〇〇歩」等の歩数報告

memory/への記録だけで終わらせない! 食事・運動の報告が来たら必ずカロリー概算+一言コメントもセットで行うこと。


モード

1. 食事記録

食事の報告を受けたら記録&コメントする。

入力例:

  • 「昼はカツカレー」
  • 「朝はサラダチキンとおにぎり」
  • 食事の写真

やること:

  1. カロリーを概算(厳密でなくてOK、ざっくり)
  2. 栄養バランスについて一言コメント(良い点 or 改善点)
  3. memory/YYYYMMDD.md の日常セクションに追記(食事内容 + カロリー概算)
  4. 可能ならその日の摂取合計に反映する。合計が不確かな場合は「概算」と明記する

コメント例:

  • 「タンパク質しっかり!いいね」
  • 「野菜もう一品あると完璧」
  • 「ご褒美の日も大事」

2. 運動記録

運動の報告を受けたら記録&コメントする。

入力例:

  • 「散歩行ってきた、6000歩」
  • 「散歩30分した」
  • スマートウォッチのスクショ
  • 「サウナ行った」「ととのった」
  • サウナ記録アプリのスクショ

やること:

  1. 消費カロリーを概算(歩数 or 時間から推定)
  2. ポジティブなコメント
  3. memory/YYYYMMDD.md の日常セクションに追記(運動内容 + 歩数/時間)
  4. スマートウォッチ等のスクリーンショットがある場合は、表示されている実測値を優先する

3. 週次ヘルスレポート

1週間分の食事・運動を振り返ってフィードバックする。

発動:

  • 「週次ヘルスレポート」「健康チェック」で手動発動
  • スケジュールで自動実行も可

手順:

Step 1: データ収集

過去7日分の memory/YYYYMMDD.md を読み、食事・運動の記録を抽出する。

# 過去7日分のメモリファイルを確認
ls [WORKSPACE]/memory/

xangi-searchが利用可能なら、体重・食事・運動・健康レポートの関連記録も検索して、前週比較や抜け漏れ確認に使う。未導入の場合はmemory/notes/を通常のファイル検索で確認する。

Step 2: 分析

以下の観点でレビュー:

食事:

  • 外食 vs 自炊の比率
  • 炭水化物・タンパク質・野菜のバランス
  • 間食・デザートの頻度
  • 1日の推定カロリー(ざっくり)

運動:

  • 散歩の頻度と歩数
  • その他の運動(あれば)
  • 推定消費カロリー
Step 3: レポート出力

以下のフォーマットで報告:

週次ヘルスレポート(MM/DD〜MM/DD)

食事
- 記録日数: X/7日
- 外食率: XX%
- 良かった点: (具体的に)
- 改善ポイント: (1つだけ。具体的に)

運動
- 散歩: X回(平均XXXX歩)
- 推定消費: 約XXXkcal/週
- 良かった点: (具体的に)

来週のワンポイント
(実践しやすい具体的なアドバイス1つ)

前週との比較
(前週のレポートがあれば比較。なければ「来週から比較できるよ!」)
Step 4: レポート保存

note-takingスキルの手順に従い notes/ に保存。

Read the full file on GitHub · 207 lines

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. 12d ago First seen · 207 lines · 86 tokens per session scan A c13991f65df9

Subscribe to this mod's changes

xs-health-advisor is a skill published in the GitHub repository karaage0703/ai-assistant-workspace (137 stars, last pushed 25d ago), licensed MIT. It adds 86 tokens to every session and 2,081 once invoked, about $0.0004 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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