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BB bilibili-all-in-one

A comprehensive Bilibili toolkit that integrates hot trending monitoring, video downloading, video watching/playback, subtitle downloading, and video publishing capabilities into a single unified skill. Supports Bilibili session cookie authentication for publishing and high-quality downloads. Requests go to official Bilibili API endpoints over HTTPS.

ClawHub Agent Skills author: zuoyunlai v1.0.0 MIT-0 18 files · 1 script body ≈ 4 787 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: when it triggers, running it twice

IntegrationMedia and videoInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
B
65/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Failures and branches w 10
50
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: bilibili-all-in-one (ClawHub)

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 · 0

✓ No critical or high findings

Files scanned: 18. 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 "type"
  • note frontmatter-key unknown frontmatter key "implementation"
  • note frontmatter-key unknown frontmatter key "interface"
  • note frontmatter-key unknown frontmatter key "runtime"
  • note frontmatter-key unknown frontmatter key "languages"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "repository"
  • note frontmatter-key unknown frontmatter key "entry_point"
  • note frontmatter-key unknown frontmatter key "required_env_vars"
  • note frontmatter-key unknown frontmatter key "optional_env_vars"
  • note frontmatter-key unknown frontmatter key "install"

Process rating: all ten parameters 65/100

  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 16 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4787 tokens
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • -243 emoji in the instructions: noise for the model
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 352: enough signal without eating the budget
  • +4Structure: 51 headings
  • +3Step-by-step instructions: 22 items
  • +3Output format is stated explicitly
  • +4Has examples (24 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This is a disclosed Bilibili toolkit with sensitive but purpose-aligned account and file capabilities, with some credential-storage and dependency hygiene cautions to review before use.
LLM: benign (high) · VirusTotal: · 14 Aug 2026