agentmods.dev

lzheng-nutrition-system

lzheng-nutrition-system is a skill for Codex from LZheng0411/Lzheng-fitness. It costs 80 tokens per session (960 once invoked), scanned A, original, MIT.

A nutrition tracking system linked to a person's training plan. It estimates meals as ranges, records entries only after user confirmation, and adjusts goals using longer-term trends.

In plain words
What is it for?
It helps set training-day and rest-day targets, estimate meals from photos or text, record confirmed nutrition, review weight and waist trends, and adjust the plan.
Why use it?
It helps avoid treating food photos or exercise-watch estimates as exact facts and keeps corrections and uncertainty visible.

Skill for Codex

Written for Codex: agents/openai.yaml present.

not rated 140repo +2 changed 1mo ago A scan SkillSpector: pass 80 tokens original MIT

Good fit It helps set training-day and rest-day targets, estimate meals from photos or text, record confirmed nutrition, review weight and waist trends, and adjust the plan.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system
View source ↗ LZheng0411/Lzheng-fitness
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 LZheng0411/Lzheng-fitness --skill lzheng-nutrition-system
Clone the repo
git clone --depth 1 https://github.com/LZheng0411/Lzheng-fitness

Made for: 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 lzheng-nutrition-system

README.md
[![agentmods](https://agentmods.dev/badge/skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system/github.svg)](https://agentmods.dev/skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system)
Your own site
<a href="https://agentmods.dev/skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system"><img src="https://agentmods.dev/badge/skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system/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 lzheng-nutrition-system

Your own site · 80×15
<a href="https://agentmods.dev/skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system"><img src="https://agentmods.dev/badge/skills/lzheng0411/lzheng-fitness/lzheng-nutrition-system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 960 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 $0.00080 $0.00960
Opus 5.5 $0.00032 $0.00384
Sonnet 5.5 $0.00016 $0.00192
Haiku 4.5 $0.00008 $0.00096

Measured 1mo ago against content hash e593611520ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lzheng-nutrition-system 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.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/test_nutrition_system.py, scripts/update_planner.py, scripts/validate_nutrition_contract.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/lzheng-nutrition-system/SKILL.md · 58 lines

What it actually says

Lzheng 通用营养系统

本 Skill 只负责营养建档、nutrition_contract、日型目标和复盘候选。训练计划决定日型，不按单次训练手表消耗临时补吃；工作台负责展示和记录，不能反向发明处方。

开始前

  1. 完整读取 营养协议。
  2. 读取当前训练计划的真实日期排程、最近体重/腰围趋势、执行率、训练表现和已确认餐食；缺失或过期时标为待校准。
  3. 营养变量按需读取 ../lzheng-training-expert-library 的 Alan Aragon 模块。
  4. 先确认目标、年龄、身高、当前体重、饮食环境、预算、医生已确认限制和主要执行障碍；未收敛前不输出精确热量。

用户流程

建档 → 得到当天目标 → 拍照或文字记录 → 查看区间估算 → 饭后反馈 → 用户确认入账 → 查看剩余 → 两周复盘

  • 照片输出只能是候选区间、置信度和误差来源。
  • estimate 是上桌总量，consumed_estimate 是实际摄入候选，confirmed_nutrition 才是正式入账。
  • 只有用户主动创建任务并显式运行一次 Agent 才允许识别；空队列不调用模型，网页不自动轮询。
  • 用户可以在候选区间内做确定性微调并保留 agent_best / user_adjusted / user_manual 来源。
  • 已确认记录的更正必须留痕；不能静默覆盖原值。

固定边界

  • 热量公式只是起点，至少用两周同条件体重趋势、腰围、训练表现和执行率校准。
  • 当前体重未知时保留 awaiting_profile，不生成伪精确目标。
  • 蛋白质和脂肪保持相对稳定，训练日型主要调整碳水；七日加权平均必须符合周目标。
  • 食堂、外卖和照片估算始终保留范围；压力进食后不使用禁食或惩罚性有氧补偿。
  • 医疗、肾脏疾病、糖尿病、进食障碍、孕期、过敏或药物相关需求转交合格专业人员；急性严重症状立即就医。
  • 个人照片、账号、密钥、环境 ID、Notion 地址和真实餐食数据不得进入公开模板或示例。

生成与交接

验证结构化协议：

python scripts/validate_nutrition_contract.py <nutrition-contract-vNN.json>

协议通过且用户确认后，保存为当前系统的营养主源，并创建 nutrition_contract_updated 交接给 lzheng-fitness-workbench-builder。交接只传相对路径和确认状态；工作台刷新、发布副本、部署和线上验证必须分别报告。

完成闸门

  1. validator 与 test_nutrition_system.py 通过；
  2. 当天日型来自真实日期排程，未知日期不猜测；
  3. 周平均、宏量换算和调整上限通过测试；
  4. 估算、实际摄入候选与确认入账三段没有混用；
  5. 默认无自动触发器、无后台空查、无自动确认；
  6. 示例保持匿名且体重为 null，不得出现虚构处方或私人配置。

视频学习与三餐报餐

用户要把学到的饮食方法用于三餐、文字/照片报餐或标签复用时，读取 学习与报餐。保留用户接受的方法和目标版本，不用新的菜单替换计算依据。

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 1mo ago Changed · +4 lines e593611520ee
  2. 2mo ago First seen · 54 lines · 80 tokens per session scan A e875ba25dc83

Subscribe to this mod's changes

lzheng-nutrition-system is a skill published in the GitHub repository LZheng0411/Lzheng-fitness (140 stars, last pushed 6d ago), licensed MIT. It adds 80 tokens to every session and 960 once invoked, about $0.0003 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 2026-09-03.

Productivity
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