SKILLEMALL.ai

BC blind-date-mirror

Scan someone's public social media profiles before a date — generate a data-driven "Date Intel Report" with personality traits, interests, lifestyle, values, red/green flags. Not stalking — just reading what they chose to make public, but more carefully than you would. 约会/相亲前扫一下对方的公开社交主页,生成一份数据驱动的「相亲情报简报」:性格推测、兴趣分布、生活方式、价值观倾向、红绿旗标记。不是偷窥——只是比你自己更仔细地读了 TA 公开展示的信息。

ClawHub Agent Skills author: Sophieyou v1.0.0 MIT-0 9 files · 1 script body ≈ 1 771 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

GeneratorData and analyticsInfrastructureMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
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 · 0

✓ No critical or high findings

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 "depends"

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. 62 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1771 tokens
  • 100Running it twice. No mutating operations
  • low 12 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
  • -243 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 364: enough signal without eating the budget
  • +4Structure: 36 headings
  • +3Step-by-step instructions: 62 items
  • +4Has examples (11 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill is advertised as public dating-profile review, but bundled collectors can use the active browser login to gather sensitive account histories such as likes, favorites, follows, ratings, and comments.
LLM: suspicious (high) · VirusTotal: · 29 May 2026