SKILLEMALL.ai

CB jobbank-search

Make sure to use this skill whenever the user mentions anything related to job searching on Akademikernes Jobbank, jobbank.dk, or looking for academic or highly educated positions in Denmark — even if they don't mention jobbank.dk explicitly. Also invoke this skill for questions about Danish job listings, graduate trainee positions, Ph.d. jobs, or finding work in specific industries or regions in Denmark. Trigger phrases include: jobbank, akademikernes jobbank, jobs denmark, academic jobs denmark, find job denmark, highly educated jobs, graduate job denmark, trainee position denmark, ph.d. position denmark, postdoc denmark, studiejob, fuldtidsjob, deltidsjob, vikariat, freelance job, praktikplads, job søgning, jobsøgning, søg job, ledige stillinger, nye jobs, it jobs denmark, engineering jobs denmark, marketing jobs denmark, finance jobs denmark, healthcare jobs denmark, remote job denmark, fjernarbejde, job københavn, job aarhus, job odense, nyuddannede job, job til nyuddannede, international job denmark, jobbank søgning, find stilling, data scientist job, software developer job, projektleder stilling, konsulent job, data analyse job.

MadsLorentzen/ai-job-search Agent Skills author: MadsLorentzen MIT 21 files · 16 scripts body ≈ 1 367 tokens Open the sourcegithub.com↗ analyzed 35 h ago

Make sure to use this skill whenever the user mentions anything related to job searching on Akademikernes Jobbank, jobbank.dk, or looking for academic or…

As a process B 73/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

GeneratorResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
58
Run on models
none yet
Process rating
B
73/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Failures and branches w 10
50
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: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1154 chars, limit 1024
  • note frontmatter-key unknown frontmatter key "enabled"

Process rating: all ten parameters 73/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1367 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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 1153: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 27 items
  • +3Output format is stated explicitly
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.