draft-slts

draft-slts is a skill for Claude Code, Codex from Andamio-Platform/coach. It costs 15 tokens per session (1,430 once invoked), scanned A, original, MIT.

A course-writing tool that drafts Student Learning Targets, which are clear statements of what learners should be able to do and show. It bases them on the course topic, audience, and learning goals.

In plain words
What is it for?
Use it when starting a course or module and you need learning targets that follow Andamio conventions.
Why use it?
It helps turn broad teaching goals into specific, assessable learning outcomes and checks them against existing patterns and research guidance.

Skill for Claude CodeCodex

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the coach plugin — 15 skills shipped together

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 skills/andamio-platform/coach/draft-slts
Any agent
npx skills add Andamio-Platform/coach --skill draft-slts
Clone the repo
git clone --depth 1 https://github.com/Andamio-Platform/coach

Made for: Claude Code, Codex.

Or install coach, the plugin that ships this one along with the rest of its 15 skills.

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 draft-slts

README.md
[![agentmods](https://agentmods.dev/badge/skills/andamio-platform/coach/draft-slts.svg)](https://agentmods.dev/skills/andamio-platform/coach/draft-slts)
Your own site
<a href="https://agentmods.dev/skills/andamio-platform/coach/draft-slts"><img src="https://agentmods.dev/badge/skills/andamio-platform/coach/draft-slts.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,430 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 $0.00015 $0.01430
Opus 5 $0.00008 $0.00715
Sonnet 5 $0.00003 $0.00286
Haiku 4.5 $0.00002 $0.00143

Measured 4d ago against content hash b794565ee418, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

draft-slts 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 4d 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/draft-slts/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Draft Student Learning Targets

Description

Generates well-formed Student Learning Targets (SLTs) for a course or module based on topic, audience, and learning goals. Follows education research best practices and Andamio protocol conventions.

Instructions

Path Resolution

Resolve file paths based on your execution context:

  • Plugin context (${CLAUDE_PLUGIN_ROOT} is set): Read knowledge from ${CLAUDE_PLUGIN_DATA}/knowledge/ (user data), falling back to ${CLAUDE_PLUGIN_ROOT}/knowledge/ (seed data). Read research from ${CLAUDE_PLUGIN_ROOT}/knowledge/research/.
  • Clone/symlink context (default): Read knowledge from knowledge/ relative to the project root (research is at knowledge/research/).

Pre-Execution Knowledge Check

Before drafting SLTs, read the knowledge base for patterns that should influence your work. If any knowledge file does not exist, skip it and proceed without prior patterns — note "No prior data available" in output.

  1. Read knowledge/slt-patterns/verb-bank.yaml

    • Note effective verbs by Bloom's level
    • Prefer verbs with high success_count
  2. Read knowledge/slt-patterns/quality-issues.yaml

    • Note problematic patterns to avoid
    • Especially avoid patterns with high frequency
  3. Surface knowledge to user (if relevant patterns exist):

    ### Tips from Previous Courses
    
    **Effective verbs at this level:** compare, distinguish, implement (12 successes)
    **Patterns to avoid:** "understand X" (flagged 8 times), task-focused phrasing
    

The user will describe a course or module they want to create. Gather the following information (ask if not provided):

  1. Topic: What is the course/module about?
  2. Audience: Who are the learners? What's their background?
  3. Learning goals: What should learners be able to do after completing this?
  4. Module count: How many modules? (Default: 3-4)
  5. SLTs per module: How many SLTs per module? (Default: 2-4)

Read the full file on GitHub · 149 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. 4d ago First seen · 149 lines · 15 tokens per session scan A b794565ee418

Subscribe to this mod's changes

draft-slts is a skill published in the GitHub repository Andamio-Platform/coach (6 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 1,430 once invoked, about $0.0001 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.

Related

Other skills, from other repositories

bq-skill

行为面试 skill。帮求职者挖掘真实经历、用 STAR/CAR 结构化、映射能力标签、构建可复用的中英双语故事库(Story Bank);并能接入 JD + 简历,针对具体岗位生成 Top 20 BQ 选题 + 基于真实经历的 STAR 准备模板(HTML 报告)。不是背答案,而是建立可复用的职业叙事体系,让任何行为面试题都能自然作答。关键词:behavioral question, BQ, 行为面试, STAR, 故事库, Amazon LP, 职业故事, tell me about a time, 面试准备, JD 面试题预测, top 20 题。.

yanliudesign/offer-toolkit-skill · 166 tokens

paper-explainer

科研论文解读:解析 arXiv/PDF 的公式与图表,提炼问题、贡献、方法、关键图和结论,再产出 B站/视频号解读视频或知乎/公众号图文。 当用户说“论文解读、讲论文、论文转视频/图文、科研科普、arXiv、学术视频”时使用。 本 SKILL 从论文做内容;video-to-article 从视频做图文,doc-convert 只转换文档格式。.

ZJU-REAL/Easel · 114 tokens

exam-study-guide

将已经讲完但尚未完成阶段门禁的一个章节整理成强类型教材清单,并在视觉模式下编译为公式可读、图片可见、知识点与全部对应例题逐项精讲的自包含 HTML/PDF。结构化工作区准备阶段完成证据、用户说 Markdown 公式仍是 raw LaTeX、图片缺失、要含课件/作业/Quiz/模拟考试题及答案的零基础讲义,或要求打印版时使用。.

ZeKaiNie/universal-examprep-skill · 113 tokens

exam-ingest

从学生上传的课件/大纲/老师勾的重点/真题,一键初始化并验证备考工作区:解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md,建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态;仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。.

ZeKaiNie/universal-examprep-skill · 116 tokens

exam-cram

临考前的极速备考总教练。把课件、大纲、重点与真题建成分章 wiki 和标准题库,再组织惰性授课、 题库判分、错题与疑难复盘及可选考前小抄,并持久化进度。用于期末、备考、突击、刷题、划重点、 错题与考前复习;不用于长期规划或与考试无关的写作/编程。.

ZeKaiNie/universal-examprep-skill · 111 tokens

exam-tutor

按章节惰性加载授课:每次只读当前阶段的一个 wiki 章节,用生活隐喻讲概念、解剖公式;重点题固定走 题面图→问题→读图量→公式→演算→答案详解→溯源七步,画图题先运行算法。用于讲懂当前章或老师勾出的重点题。.

ZeKaiNie/universal-examprep-skill · 88 tokens