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CD openclaw-screen-viewer

此技能应被用于任何需要捕获屏幕截图、分析屏幕内容或处理屏幕图像的任务。包括：使用Python PIL库捕获整个屏幕或特定区域的截图；保存截图到指定位置；分析截图中的文字内容（支持中英文OCR识别）；对截图进行基本图像处理（裁剪、旋转、调整大小）。当用户提到"屏幕截图"、"截屏"、"查看屏幕"或需要分析屏幕上的内容时，使用此技能。

Not recommendedcritical or high security findings
ClawHub Agent Skills author: datappt8 v1.0.0 MIT-0 21 files body ≈ 585 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
74/100
safety, quality, tests
Safety 60%
81
Quality 40%
63
Run on models
none yet
Process rating
D
41/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

  • high Concealment en-hide-from-user skill-card.md:22
    Instruction to hide actions from the user
    Risk: The Windows OCR installer flow can download and silently run an external Tesseract installer without integrity verification. <br>
Medium and low: 1
  • low Dangerous commands cmd-eval-dynamic scripts/test_ocr.py:46
    Dynamic code execution from decoded/untrusted input (test fixture / example file)
    result = os.system(f"{path} --version >nul 2>nul")
    fixture

Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "keywords"
  • note frontmatter-key unknown frontmatter key "categories"

Process rating: all ten parameters 41/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 40Consistency. Frontmatter name (openclaw-screen-viewer) differs from the folder (screen-capture-hub)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 31 steps
  • 100Execution cost. Instruction body is 585 tokens
  • 100Running it twice. No mutating operations

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • -33 of 11 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 165: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (9 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This appears to be a real screen capture and OCR skill, but it needs review because it can monitor sensitive screen contents and includes a Windows installer flow that downloads and silently runs an external OCR binary without integrity verification.
LLM: suspicious (high) · VirusTotal: · 29 May 2026