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BB alibabacloud-bailian-videoanalysis

Alibaba Cloud Bailian Video Analysis Skill. Use for intelligent video comprehension and analysis via the Bailian (QuanMiaoLightApp) API. **Required API Product**: QuanMiaoLightApp (version 2024-08-01) **Required API Actions**: SubmitVideoAnalysisTask, GetVideoAnalysisTask **DO NOT use**: videorecog, Mts, or any other product for video analysis Triggers: "analyze video", "understand video", "analyze the local video /temp/xxx.mp4", "analyze the local video https://xxx.com/temp/xxx.mp4", "what is this video about", "summarize this video", "split video into shots", "video comprehension", "extract video insights", "transcribe video", "extract video captions", "generate video title", "generate video outline", "video mindmap".

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.2 MIT-0 11 files body ≈ 4 703 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 77/100 · Nearly there — weak spots: running it twice, progress reporting

AnalyzerMedia and videotype 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
B
81/100
safety, quality, tests
Safety 60%
69
Quality 40%
100
Run on models
none yet
Process rating
B
77/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

    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 · 11

    ✓ No critical or high findings

    Medium and low: 11
    • medium Dangerous commands cmd-autorun-instruction references/acceptance-criteria.md:134
      Instructs the agent to auto-run a script on every session
      - Always run `check_env.py` first to ensure dependencies and credentials are ready
    • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:44
      Privilege escalation / world-writable permissions
      sudo mv aliyun /usr/local/bin/
    • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:55
      Privilege escalation / world-writable permissions
      sudo mv aliyun /usr/local/bin/
    • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:65
      Privilege escalation / world-writable permissions
      sudo mv aliyun /usr/local/bin/
    • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:75
      Privilege escalation / world-writable permissions
      sudo mv aliyun /usr/local/bin/
    • low Secrets in code secret-high-entropy-token scripts/quanmiao_get_videoAnalysis_task_result.py:14
      High-entropy token-like string (may be an id, hash or a credential)
      from alib…ent import Client as Quan…ent
    • low Secrets in code secret-high-entropy-token scripts/quanmiao_get_videoAnalysis_task_result.py:21
      High-entropy token-like string (may be an id, hash or a credential)
      def create_client() -> Quan…nt:
    • low Secrets in code secret-high-entropy-token scripts/quanmiao_get_videoAnalysis_task_result.py:34
      High-entropy token-like string (may be an id, hash or a credential)
      return Quan…ent(config)
    • low Secrets in code secret-high-entropy-token scripts/quanmiao_submit_videoAnalysis_task.py:11
      High-entropy token-like string (may be an id, hash or a credential)
      from alib…ent import Client as Quan…ent
    • low Secrets in code secret-high-entropy-token scripts/quanmiao_submit_videoAnalysis_task.py:18
      High-entropy token-like string (may be an id, hash or a credential)
      def create_client() -> Quan…nt:
    • low Secrets in code secret-high-entropy-token scripts/quanmiao_submit_videoAnalysis_task.py:31
      High-entropy token-like string (may be an id, hash or a credential)
      return Quan…ent(config)

    Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 77/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4703 tokens
    • 100Steps. 79 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Failures and branches. 12 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (7 tags): a typed call is more reliable

    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

    • +1No license
    • +2Single-language instructions
    • +5Description quotes 14 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 729: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 79 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)
    • +3All 3 scripts are documented

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

    External checks

    ClawHub: suspicious
    This skill appears to perform Alibaba Cloud video analysis as advertised, but it needs review because it uses broad cloud setup, credentials, OSS uploads, signed video URLs, and local result caching.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026