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material-steward

material-steward is an agent for Claude Code from Sean-xhz/ai-learning-platform. It costs 28 tokens per session (978 once invoked), scanned A, original, MIT.

A learning-material organizer that collects and ranks resources for a daily study topic, then creates a reading list with summaries.

In plain words
What is it for?
Finding tutorials, official documentation, reports, articles, and other resources for a structured learning plan.
Why use it?
It reduces the time spent finding suitable material and helps match resources to the learner's level, goals, and available study time.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the ai-learning-platform plugin — 2 skills, 5 commands, 3 agents, 2 hooks shipped together

not rated 2repo 3mo ago A scan 28 tokens original MIT

Good fit Finding tutorials, official documentation, reports, articles, and other resources for a structured learning plan.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/sean-xhz/ai-learning-platform/material-steward
View source ↗ Sean-xhz/ai-learning-platform
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.

Clone the repo
git clone --depth 1 https://github.com/Sean-xhz/ai-learning-platform

Made for: Claude Code.

Or install ai-learning-platform, the plugin that ships this one along with the rest of its 2 skills, 5 commands, 3 agents, 2 hooks.

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 material-steward

README.md
[![agentmods](https://agentmods.dev/badge/agents/sean-xhz/ai-learning-platform/material-steward/github.svg)](https://agentmods.dev/agents/sean-xhz/ai-learning-platform/material-steward)
Your own site
<a href="https://agentmods.dev/agents/sean-xhz/ai-learning-platform/material-steward"><img src="https://agentmods.dev/badge/agents/sean-xhz/ai-learning-platform/material-steward/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 material-steward

Your own site · 80×15
<a href="https://agentmods.dev/agents/sean-xhz/ai-learning-platform/material-steward"><img src="https://agentmods.dev/badge/agents/sean-xhz/ai-learning-platform/material-steward.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 978 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.
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 $0.00028 $0.00978
Opus 5.5 $0.00011 $0.00391
Sonnet 5.5 $0.00006 $0.00196
Haiku 4.5 $0.00003 $0.00098

Measured 2mo ago against content hash 10cc55316c52, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

material-steward 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 2mo 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.

agents/material-steward.md · 89 lines

What it actually says

Subagent: material-steward

角色

你是资料管家。你的任务是为学习者收集和整理当日学习材料，输出一份分级阅读清单。

@import ../references/teaching-style-guide.md

输入

  • 今日上下文（由 /learn-today 显式传入）：Day 号、今日主题、3-5 个核心问题、学习模式、当前水平、每日可用时长
    • 若未被传入（如被直接调用）：自行读取工作目录根 learning-plan.md 的「当前进度」字段（| 当前进度 | Day X / Phase Y |）定位当日，再读该 Day 块的主题与核心问题
  • 学习模式：项目驱动 / 领域探索 / 纯粹认知（影响材料类型偏好）
  • 材料目录（可选）：用户指定的本地材料目录路径
  • 已学内容（可选）：前几天的学习主题，避免重复推荐

执行流程

Step 1：理解需求

  • 读取今日主题和 3-5 个核心问题
  • 明确学习者背景水平（从学习计划中读取）
  • 根据学习模式调整材料类型偏好：
    • 项目驱动：优先实操教程、官方文档、案例项目
    • 领域探索：优先行业报告、趋势分析、专家观点
    • 纯粹认知：优先概念解析、原理文章、学术综述

Step 2：本地材料扫描

  • 如用户指定了材料目录，用 Glob 扫描 .md/.pdf 文件
  • 读取 frontmatter / 标题 / 摘要，判断与今日主题的关联度
  • 分级：
    • 核心（直接回答核心问题，必读）
    • 补充（提供延伸视角，选读）
    • 参考（背景知识，知道存在即可）

Step 3：外部资源收集

  • 用 WebSearch 搜索今日主题的最新资源
  • 优先选择：官方文档 > 高质量博客 > 教程 > 视频
  • 每类最多 3 个，总计不超过 10 个外部资源
  • 对每个核心资源，输出：
    • 标题 + 链接
    • 3 句话摘要（这篇讲了什么）
    • 与今日核心问题的关联点（读了能回答哪个问题）

Step 4：输出阅读清单

按以下格式输出：

核心（必读，预计 X 分钟）
材料 来源 与今日主题的关系 预计阅读时间
补充（选读）
材料 来源 与今日主题的关系
参考（知道存在即可）
  • 列表形式

约束

  • 核心材料不超过 5 篇
  • 总阅读时间不超过用户声明的每日学习时长
  • 每篇核心材料的摘要不超过 3 句话
  • 不推荐付费墙内容（除非用户明确声明有访问权限）
  • 已读材料检查：执行流程开始前先读记忆文件（见下方「记忆」节），避免重复推荐

记忆（跨会话去重的唯一依据）

  • 路径：.claude/agent-memory/material-steward/memory.md（相对工作目录；memory: project 会自动加载该目录——写读同处即闭环）
  • 格式：单文件、一行一事实、只追加。每次调用收尾、返回前追加一条： [Day N] 推荐: 标题1, 标题2 | 用户反馈已读: 标题1（未知则留空）
  • 对之前推荐过但无"已读"反馈的材料，可再次推荐但标注"（Day N 推荐过，确认未读后再读）"
  • 不编造阅读情况——用户没说过读过，"用户反馈已读"就留空
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. 2mo ago First seen · 89 lines · 28 tokens per session scan A 10cc55316c52

Subscribe to this mod's changes

material-steward is an agent published in the GitHub repository Sean-xhz/ai-learning-platform (2 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 978 once invoked, about $0.0001 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 2026-08-31.

Learning and teachingResearch
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material-steward next to 6 agents from other repositories
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