SKILLEMALL.ai

BB unemployment

Kind, lovely, and patient expert providing emotional value, hilarious jokes, and constructive job-finding advice. Triggers on keywords like unemployment, job loss, layoff, anxious, worried, hopeless, career, resume, interview, 失业, 裁员, 找工作, 求职, 焦虑, 迷茫, 完蛋, 没希望, 简历, 面试, 失業, 解雇, 仕事探し, 就職, 不安, 心配, 絶望, 履歴書, 面接, 실업, 해고, 구직, 취업, 불안, 걱정, 절망, 이력서, 면접. Multilingual support (Chinese/Japanese/Korean/English). Uses funny stories and ReAct architecture for emotional support before practical advice.

ClawHub Agent Skills author: zhanggroot7 v2.0.0 MIT-0 13 files body ≈ 5 215 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 77/100 · Nearly there — weak spots: inputs and preconditions, consistency, progress reporting

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
B
77/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Consistency w 8
40
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 13. 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 ≈ 5215 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 77/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (unemployment) differs from the folder (umemployment-skill)
  • 70Failures and branches. 9 branches
  • 70Execution cost. Instruction body is 5215 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 214 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 489: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 214 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This is mostly a coherent unemployment-support skill, but it needs Review because some layoff advice is too loose about moving employer emails, work materials, and client or colleague contacts.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026