Agent skill

Grad Tpack

by asgard-ai-platform in asgard-ai-platform/skills

Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge.

MITAuto-check passedEducation

Install Grad Tpack

skills CLI

$ npx skills add asgard-ai-platform/skills --skill grad-tpack -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install asgard-ai-platform/skills grad-tpack --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/grad-tpack .claude/skills/grad-tpack && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "grad-tpack" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack into .claude/skills/grad-tpack/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "grad-tpack", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add asgard-ai-platform/skills --skill grad-tpack -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install asgard-ai-platform/skills grad-tpack --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/grad-tpack .agents/skills/grad-tpack && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "grad-tpack" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack into .agents/skills/grad-tpack/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "grad-tpack", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add asgard-ai-platform/skills --skill grad-tpack -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install asgard-ai-platform/skills grad-tpack --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/grad-tpack .cursor/skills/grad-tpack && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "grad-tpack" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack into .cursor/skills/grad-tpack/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "grad-tpack", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/asgard-ai-platform/skills.git --path grad-tpack

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add asgard-ai-platform/skills --skill grad-tpack -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install asgard-ai-platform/skills grad-tpack --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/grad-tpack .gemini/skills/grad-tpack && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "grad-tpack" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack into .gemini/skills/grad-tpack/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "grad-tpack", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install asgard-ai-platform/skills grad-tpack

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add asgard-ai-platform/skills --skill grad-tpack -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/grad-tpack .github/skills/grad-tpack && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "grad-tpack" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack into .github/skills/grad-tpack/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "grad-tpack", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add asgard-ai-platform/skills --skill grad-tpack -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install asgard-ai-platform/skills grad-tpack --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/grad-tpack .opencode/skills/grad-tpack && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "grad-tpack" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/grad-tpack into .opencode/skills/grad-tpack/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "grad-tpack", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: grad-tpack
GitHub stars: 242
Token cost: ~1.1k tokens
SKILL.md length: 354 words
Files: 4 (incl. references)
Skills in repo: 207
Repo updated: Jun 6, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge.

Works in 4 steps: Map Knowledge Domains → Identify Integration Opportunities → Design at the TPACK Intersection → …
The user needs to assess teacher readiness for technology integration
SKILL.md covers Overview, When to Use, Assumptions and Methodology, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grad Tpack is an agent skill from asgard-ai-platform/skills. Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge. Use this skill when the user needs to assess teacher readiness for technology integration, design professional development for ed-tech, or evaluate whether technology use is pedagogically grounded — even if they say 'how to integrate technology in teaching', 'ed-tech evaluation', or 'teacher technology competency'.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/lesson-design.md` and `references/tpack-instruments.md`).

It sits in Education. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

The user needs to assess teacher readiness for technology integration
Design professional development for ed-tech
Evaluate whether technology use is pedagogically grounded — even if they say how to integrate technology in teaching
Ed-tech evaluation

Example prompts

“how to integrate technology in teaching”
“ed-tech evaluation”
“teacher technology competency”
“/grad-tpack”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

Map Knowledge Domains
Identify Integration Opportunities
Design at the TPACK Intersection
Evaluate and Iterate

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Grad Tpack loads about 1.1k tokens when it runs, and up to ~7.2k if it reads all its reference files. Until then it costs about 121 tokens; SKILL.md has 354 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~121
When it runs · the whole SKILL.md, loaded when a task matches: ~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~7.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 354 words, ~1,150 tokens.

Download SKILL.mdSave it as .claude/skills/grad-tpack/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: grad-tpack
description: Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge. Use this skill when the user needs to assess teacher readiness for technology integration, design professional development for ed-tech, or evaluate whether technology use is pedagogically grounded — even if they say 'how to integrate technology in teaching', 'ed-tech evaluation', or 'teacher technology competency'.
metadata.category: WP-33 傳播/教育/公共行政
metadata.tags: education, tpack, educational-technology, teacher-knowledge

TPACK Framework

Overview

TPACK (Technological Pedagogical Content Knowledge) describes the knowledge teachers need for effective technology integration. It identifies seven knowledge domains formed by the intersections of Technology (TK), Pedagogy (PK), and Content (CK) knowledge, arguing that effective integration requires understanding all three simultaneously.

When to Use

Trigger conditions:

Evaluating whether technology use in instruction is pedagogically sound
Designing teacher professional development for technology integration
Assessing gaps in educator knowledge domains

When NOT to use:

When classifying learning objectives by cognitive level (use Bloom's taxonomy)
When designing scaffolded learning experiences (use constructivism)
When evaluating information system quality (use IS Success Model)

Assumptions

IRON LAW: Effective Technology Integration Requires ALL THREE Knowledge Types

Technology without pedagogy or content is just a tool, not instruction.
The seven domains:
  TK — Technology Knowledge (how tools work)
  PK — Pedagogical Knowledge (how to teach)
  CK — Content Knowledge (what to teach)
  TPK — How technology enables pedagogical strategies
  TCK — How technology represents content
  PCK — How to teach specific content (Shulman)
  TPACK — The intersection of ALL three: the sweet spot
Weakness in ANY domain degrades technology integration quality.

Methodology

Step 1: Map Knowledge Domains

Assess the current state of each knowledge domain (TK, PK, CK) and their intersections for the instructor or instructional context.

Step 2: Identify Integration Opportunities

Find where technology can genuinely enhance pedagogy for specific content. Ask: "What can students do WITH technology that they couldn't do WITHOUT it?"

Step 3: Design at the TPACK Intersection

Create learning activities where technology choice is driven by pedagogical purpose AND content requirements, not technology novelty.

Step 4: Evaluate and Iterate

Assess whether the technology integration achieved learning goals. Check: Did technology serve the pedagogy? Did it represent content accurately? Was it accessible?

Output Format

markdown

# TPACK Analysis: {Context/Course}

## Knowledge Domain Assessment
| Domain | Current State | Evidence | Gap |
|--------|-------------|----------|-----|
| TK | ... | ... | ... |
| PK | ... | ... | ... |
| CK | ... | ... | ... |
| TPK | ... | ... | ... |
| TCK | ... | ... | ... |
| PCK | ... | ... | ... |
| TPACK | ... | ... | ... |

## Technology Integration Design
- Content goal: {what students should learn}
- Pedagogical strategy: {how they will learn it}
- Technology role: {why this technology, specifically}
- TPACK alignment: {how all three intersect}

## Recommendations
{Targeted development for weakest domains}

Show full SKILL.md (145 more words)Show less

Gotchas

Technology for technology's sake: The most common TPACK violation. Adding technology without clear pedagogical purpose (e.g., PowerPoint replacing a blackboard with no pedagogical change) is TK without TPK or TPACK.
TPACK is context-specific: A teacher may have strong TPACK for one topic and weak TPACK for another. It's not a general trait — it varies by content area and technology type.
Measurement challenges: TPACK is typically measured via self-report surveys, which inflate scores. Observation-based and performance-based assessments are more valid but harder to scale.
Rapid technology change: TK decays quickly as technology evolves. TPACK development must be ongoing, not a one-time training event.
PCK is the foundation: Shulman's PCK (knowing how to teach specific content) predates and underlies TPACK. Teachers weak in PCK cannot develop strong TPACK regardless of technology skills.

References

For TPACK measurement instruments, see references/tpack-instruments.md
For TPACK lesson design templates, see references/lesson-design.md

Files

SKILL.md and 3 other files (references) in grad-tpack of asgard-ai-platform/skills.

SKILL.md
examples/sample_scenario.md
references/lesson-design.md
references/tpack-instruments.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Grad Tpack next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Grad Tpack compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Grad Tpack this skillasgard-ai-platform/skills	242	—	~1.1k	Automated safety check: Pass	MIT	4 mo ago
DeepTutor CLIHKUDS/DeepTutor	41k	—	~2.8k	Automated safety check: Pass	Apache-2.0	3 days ago
AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch	67k	—	~2k	Automated safety check: Pass	MIT	today
Deep Reading Analystginobefun/deep-reading-analyst-skill	354	4 repos	~3.6k	Automated safety check: Pass	MIT	11 mo ago
OpenMAIC Setup and ExtensionTHU-MAIC/OpenMAIC	40k	—	~1.7k	Automated safety check: Notes	MIT	today
Codebase to Coursezarazhangrui/codebase-to-course	5.7k	—	~4.4k	Automated safety check: Pass	None	6 mo ago

Similar skills

DeepTutor CLI
HKUDS/DeepTutor
Teaches the agent to set up and run DeepTutor from the command line: chat and capabilities, knowledge bases, partners, memory, sessions, notebooks and the server or Web app.
41k GitHub stars~2.8k tokensUpdated 3 days ago
EducationAuto-check passed
AI Engineering Placement Quiz
rohitg00/ai-engineering-from-scratch
Runs a 10-question quiz across five areas to place a learner in the AI Engineering from Scratch curriculum, so they skip what they already know.
67k GitHub stars~2k tokensUpdated today
EducationAuto-check passed
Deep Reading Analyst
ginobefun/deep-reading-analyst-skill
Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems…
354 GitHub starsUsed in 4 repos~3.6k tokens
EducationAuto-check passed
OpenMAIC Setup and Extension
THU-MAIC/OpenMAIC
Guides setup, classroom generation and secondary development for OpenMAIC, the multi-agent interactive classroom, one confirmed phase at a time.
40k GitHub stars~1.7k tokensUpdated today
EducationAuto-check: notes
Codebase to Course
zarazhangrui/codebase-to-course
Turns a codebase into an interactive single-page HTML course for non-technical learners, with scroll modules, animated diagrams, quizzes and plain-English code translations.
5.7k GitHub stars~4.4k tokensUpdated 6 mo ago
EducationAuto-check passed
AI Engineering Project Tutor
rohitg00/ai-engineering-from-scratch
Tutors a learner through one stage of a hands-on AI engineering project per session: lesson, prediction, code, grader run and reflection, with hints but never full solutions.
67k GitHub stars~1.6k tokensUpdated today
EducationAuto-check passed

Questions about Grad Tpack

What does Grad Tpack do?

Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge. Grad Tpack is an agent skill from asgard-ai-platform/skills. Apply the TPACK framework to evaluate and design technology-integrated instruction at the intersection of technological, pedagogical, and content knowledge.

When should I use Grad Tpack?

Grad Tpack fits situations like: the user needs to assess teacher readiness for technology integration; design professional development for ed-tech; evaluate whether technology use is pedagogically grounded — even if they say how to integrate technology in teaching; ed-tech evaluation.

How do I install Grad Tpack in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill grad-tpack -a claude-code`. Or copy the skill folder (grad-tpack in asgard-ai-platform/skills) into .claude/skills/grad-tpack in your project. Claude Code loads it when a task matches its description.

How do I install Grad Tpack in Codex?

Run `npx skills add asgard-ai-platform/skills --skill grad-tpack -a codex`. Or copy the skill folder (grad-tpack in asgard-ai-platform/skills) into .agents/skills/grad-tpack in your project. Codex loads it when a task matches its description.

Can I use Grad Tpack in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill grad-tpack -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/grad-tpack, .gemini/skills/grad-tpack, .github/skills/grad-tpack and .opencode/skills/grad-tpack in your project.

What does Grad Tpack need to run?

SKILL.md names no scripts, command-line tools or credentials: Grad Tpack is instructions for the agent only.

Does Grad Tpack access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Grad Tpack safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Grad Tpack use?

Grad Tpack is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Grad Tpack use?

About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.1k tokens, read only when the agent opens those files.

What are the alternatives to Grad Tpack?

Skills that share tags, products or a category with Grad Tpack: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 67k stars), Deep Reading Analyst (ginobefun/deep-reading-analyst-skill, 354 stars) and OpenMAIC Setup and Extension (THU-MAIC/OpenMAIC, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grad Tpack?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Grad Tpack

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

TPACK Framework

Overview

When to Use

Assumptions

Methodology

Step 1: Map Knowledge Domains

Step 2: Identify Integration Opportunities

Step 3: Design at the TPACK Intersection

Step 4: Evaluate and Iterate

Output Format

Gotchas

References

Files

Compare with similar skills

Similar skills

More from asgard-ai-platform/skills

Related

Questions about Grad Tpack