SKILLEMALL.ai

BC photo-downloader

批量下载豆瓣电影/电视剧/综艺的剧照和海报。输入片名自动搜索下载,完全自动化,不需要登录。支持缓存去重、反爬延迟。当用户提到"下载剧照"、"获取海报"、"批量下载图片"时使用。

ClawHub Agent Skills author: z_j v1.0.1 MIT-0 5 files body ≈ 572 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
98
Quality 40%
63
Run on models
none yet
Process rating
C
53/100
Has gaps
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

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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Dangerous commands cmd-privilege auto-download.js:182
    Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
    args: ['--no-sandbox', '--disable-setuid-sandbox']
    detectorcode literal
  • low Dangerous commands cmd-privilege auto-download.js:254
    Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
    args: ['--no-sandbox', '--disable-setuid-sandbox']
    detectorcode literal

Files scanned: 5. 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 "security_warning"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 572 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)
  • +3Description length 88: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -212 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (5 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This skill mostly does what it claims, but it can automatically run an unpinned npm install during normal use and has confusing privacy/session documentation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026