BF autoglm-toolkit
AutoGLM AI agent toolkit powered by Zhipu AI. Includes browser automation, deep research, web search, image generation, image search, and web page content extraction. Perfect for Chinese internet tasks. Triggers: "浏览器自动化", "深度研究", "网络搜索", "AI生图", "搜图", "网页抓取", "AutoGLM", "智谱".
As a process F 41/100 · Will not run — References files that are not bundled: image_url
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
For the model run — optional
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: image_url - note
frontmatter-keyunknown frontmatter key "env"
Process rating: all ten parameters 41/100
Will not run. References files that are not bundled: image_url
- 0Tools and files. 1 referenced file(s) missing: image_url
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1563 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 280: enough signal without eating the budget
- +4Structure: 31 headings
- +3Step-by-step instructions: 38 items
- +3Output format is stated explicitly
- +4Has examples (12 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.
External checks
ClawHub: suspicious
This skill is a broad AutoGLM automation toolkit that appears purpose-aligned, but it can act through logged-in browser sessions and reuse them, so users should review it carefully before installing.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026