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CD video-downloader-by-browser

“手动介入式分片视频下载：用有头浏览器（用户可见、不自动关闭）打开视频页，拦截真实流地址，多路并行高速下载分片（TS 流 / m3u8 / 大分片 MP4），无损合并为完整 MP4，验收通过后再清理分片。面向需要分片下载的流媒体视频，尤其是需要登录、短信验证码、滑动验证、观看密码或切换清晰度的受限站点（优酷、腾讯视频、爱奇艺、B 站等）。关键词：下载视频、视频下载、优酷下载、需要登录的视频、需要密码的视频、m3u8、ts 分片合并”

ClawHub Agent Skills author: sedey999 v1.3.0 MIT-0 33 files · 10 scripts body ≈ 5 148 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

“手动介入式分片视频下载：用有头浏览器（用户可见、不自动关闭）打开视频页，拦截真实流地址，多路并行高速下载分片（TS 流 / m3u8 / 大分片 MP4），无损合并为完整…

As a process D 36/100 · Unfinished process — References files that are not bundled: scripts/node_modules/, scripts/<platform>_collect.py, references/<platform>.md

ProcedurePlaywrightMedia 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
C
78/100
safety, quality, tests
Safety 60%
94
Quality 40%
53
Run on models
none yet
Process rating
D
36/100
Unfinished process
References files that are not bundled: scripts/node_modules/, scripts/<platform>_collect.py, references/<platform>.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Write Edit Bash
  • low Secrets in code secret-password-literal scripts/browser_ctl.mjs:381
    Hard-coded password / key literal (may be an example)
    const pwd = line.slice(7).trim();

Files scanned: 17. 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")
  • warning body-long SKILL.md body ≈ 5148 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/node_modules/
  • warning missing-ref reference to a missing file: scripts/<platform>_collect.py
  • warning missing-ref reference to a missing file: references/<platform>.md
  • warning missing-ref reference to a missing file: scripts/<platform>_*.py
  • warning missing-ref reference to a missing file: scripts/node_modules
  • note frontmatter-key unknown frontmatter key "created"
  • note frontmatter-key unknown frontmatter key "updated"

Process rating: all ten parameters 36/100

Will not run. References files that are not bundled: scripts/node_modules/, scripts/<platform>_collect.py, references/<platform>.md
  • 0Tools and files. 5 referenced file(s) missing: scripts/node_modules/, scripts/<platform>_collect.py, references/<platform>.md
  • 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
  • 20When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 5148 tokens
  • 100Steps. 87 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 11 top-level sections: this looks like several domains in one skill

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
  • -230 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 218: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 87 items
  • +4Has examples (16 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 10 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.

External checks

ClawHub: suspicious
This skill is a coherent video downloader, but it handles browser sessions, cookies, and password-related data in ways that are too broad and persistent for automatic approval.
LLM: suspicious (high) · 25 Sept 2026