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.
npx skills add zai-org/GLM-skills --skill glm-master-skillgit clone --depth 1 https://github.com/zai-org/GLM-skillsWrote 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.
[](https://agentmods.dev/skills/zai-org/glm-skills/glm-master-skill)<a href="https://agentmods.dev/skills/zai-org/glm-skills/glm-master-skill"><img src="https://agentmods.dev/badge/skills/zai-org/glm-skills/glm-master-skill/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.
<a href="https://agentmods.dev/skills/zai-org/glm-skills/glm-master-skill"><img src="https://agentmods.dev/badge/skills/zai-org/glm-skills/glm-master-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.01870 |
| Opus 5 | $0.00023 | $0.00935 |
| Sonnet 5 | $0.00009 | $0.00374 |
| Haiku 4.5 | $0.00005 | $0.00187 |
Grade A, and why
glm-master-skill 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GLM Master Skill (Guide Only) / GLM 技能总览（仅指南）
This is a documentation-only master skill.
- ✅ It introduces available GLM skills.
- ✅ It provides official install links and commands.
- ❌ It does not run any local scripts.
- ❌ It does not use subprocess.
本 Skill 只做导航与安装说明，不执行任何本地脚本。
Official Skills Catalog / 官方技能目录
GLM-OCR
| Skill | Purpose | Link |
|---|---|---|
glmocr |
General OCR (text extraction) | https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr |
glmocr-table |
Table extraction | https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr-table |
glmocr-formula |
Formula extraction | https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr-formula |
glmocr-handwriting |
Handwriting OCR | https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr-handwriting |
glmocr-sdk |
GLM-OCR SDK guidance | https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr-sdk |
GLM-Image
| Skill | Purpose | Link |
|---|---|---|
glm-image-gen |
Text-to-image generation | https://github.com/zai-org/GLM-skills/tree/main/skills/glm-image-gen |
GLM-V
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.
- 10d ago First seen · 183 lines · 45 tokens per session scan A 6255fef50b37
glm-master-skill is a skill published in the GitHub repository zai-org/GLM-skills (474 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,870 once invoked, about $0.0002 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.
Other skills, from other repositories
vision-skills
Local vision CLIs: glance (describe/ask/OCR an image), ground (locate a target, pixel box), detect (element inventory), trace (image to SVG geometry), crop (cut a pixel box to a file), and scripts/htmlshot.py (HTML file to image). Use for any task involving an image — questions, text, splitting and transcribing long…
vision
Nested swiss-knife reference for image understanding — a decision tree that routes between three paths depending on what the agent has access to: (1) the built-in vision tool if the LLM provider supports image input, (2) the sibling minimax-cli reference if a usable MiniMax preset/key slot is available, or (3) a local…
watch
Watch any video (URL, stream, or local path) via Watch Skill. Downloads, extracts scene-aware deduped frames, OCRs them, transcribes (captions first, then local Whisper — offline by default), indexes everything, and hands the result to the agent. Follow-up questions are answered from the persistent index without…
asking-with-evidence
The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Use this to answer from the persistent index with timestamped evidence and a confidence score instead of re-watching or guessing.
configuring-vision
The user wants to connect an LLM or vision provider, already has an API key, asks "can I use OpenAI/Anthropic/Gemini/OpenRouter", wants local Ollama, or needs different cheap and strong models. Use this to configure provider-neutral visual understanding without tying Watch Skill to one agent or model vendor.
the-loop
The user built or changed something visual — a UI, an animation, a game, a generated video — and wants it verified, or asks "why does my UI look wrong", "check that the fix actually worked", "does the animation glitch". Use this to record the running thing, critique the recording against plain-language pass criteria…