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B站AI信息源 — 每日扫描B站AI相关账号，按点赞量发现爆款视频，智能聚类话题后生成包含封面图、互动数据与订阅支持的HTML日报。同时基于热门话题执行AI情报调查，采用多引擎搜索与交叉验证，输出结构化调查报告。支持用户自定义关键词定向查询。⚠️数据每日15:00更新前一天数据，目标日期无数据时必须先告知用户并等待确认后才能调用接口，禁止自动获取。当用户需要AI-B站日报、B站爆款、AI-B站热点、B站AI内容、B站AI视频、B站情报或自定义关键词查询时使用。

ClawHub Agent Skills author: RedFox v1.0.2 MIT-0 10 files body ≈ 1 689 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

B站AI信息源 —…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentstype 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
84/100
safety, quality, tests
Safety 60%
90
Quality 40%
74
Run on models
none yet
Process rating
D
46/100
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

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

  1. 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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Dangerous commands cmd-persistence assets/daily_report.py:1181
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    f'(crontab -l 2>/dev/null; echo "{cron_line}") | crontab -',
    code literal
  • low Dangerous commands cmd-shell-rc assets/daily_report.py:171
    Writes to a shell startup file (string literal in code, not executed)
    print(f"  macOS/Linux (zsh):  echo 'export {ENV_KEY}=ak_你的密钥' >> ~/.zshrc && source ~/.zshrc")
    code literal
  • low Dangerous commands cmd-shell-rc assets/daily_report.py:172
    Writes to a shell startup file (detector / deny-list definition; string literal in code, not executed)
    print(f"  macOS/Linux (bash): echo 'export {ENV_KEY}=ak_你的密钥' >> ~/.bashrc && source ~/.bashrc")
    detectorcode literal
  • low Dangerous commands cmd-cron-mention assets/daily_report.py:1181
    Mentions editing / listing crontab (string literal in code, not executed)
    f'(crontab -l 2>/dev/null; echo "{cron_line}") | crontab -',
    code literal
  • low Dangerous commands cmd-cron-mention assets/daily_report.py:1211
    Mentions editing / listing crontab (string literal in code, not executed)
    f'crontab -l 2>/dev/null | grep -v "{script_path}" | crontab -',
    code literal
  • low Dangerous commands cmd-cron-mention assets/daily_report.py:1217
    Mentions editing / listing crontab (string literal in code, not executed)
    warn("自动移除 crontab 失败，请手动执行: crontab -e")
    code literal

Files scanned: 10. 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")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1689 tokens
  • 100Running it twice. No mutating operations
  • 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
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 232: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill is mostly a Bilibili AI report generator, but its optional subscription mode and investigation instructions create review-worthy privacy and credential risks.
LLM: suspicious (high) · VirusTotal: · 16 Jun 2026