SKILLEMALL.ai

BB upcycle-your-job

Anna Meller's "#Upcycle Your Job: The Smart Way to Balance Family Life and Career" — a research-backed 6-step PROPEL model for working mothers to upcycle their corporate career instead of quitting. Covers 5 use cases: ① Work-life balance clarity — ("I can't balance work and family" "I'm burning out" "mom guilt" "I need a better schedule") ② Flexible working negotiation — ("how to ask for flexible hours" "negotiate part-time" "job crafting" "remote work proposal") ③ Career continuity after motherhood — ("back from maternity leave" "return to work" "mommy track escape" "career break returner") ④ Corporate culture navigation — ("man made workplace" "implicit bias at work" "unconscious bias" "always-on culture") ⑤ Self-coaching through the PROPEL model — ("PROPEL model" "work-life assessment" "Balanced Leader" "life career rainbow") Trigger when users say: "work-life balance" "working mom" "return to work" "flexible working" "mommy track" "corporate career" "maternity leave return" "career pause" "working mother burnout" "job craft" "time management for parents" "Anna Meller" "lean in my terms" "PROPEL" "upcycle your job"

ClawHub Agent Skills author: BestBooks v1.0.0 MIT-0 8 files body ≈ 2 389 tokens Open the sourceclawhub.ai analyzed 33 h ago

Anna Meller's "Upcycle Your Job: The Smart Way to Balance Family Life and Career" — a research-backed 6-step PROPEL model for working mothers to upcycle their…

As a process B 66/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1135 chars, limit 1024

Process rating: all ten parameters 66/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 34 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2389 tokens
  • 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 1135: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 36 example trigger phrases
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: clean
This appears to be a text-only career-coaching skill whose main risk is over-broad or identity-assumptive guidance, not malware or hidden system access.
LLM: benign (medium) · VirusTotal: · 8 Jun 2026