SKILLEMALL.ai

AC job-hunter

LinkedIn job search assistant that scrapes listings, filters by technologies and countries, and scores matches with AI. Use when the user wants to find jobs, search for job openings, look for work, job hunt, or find career opportunities. Triggers on phrases like "find jobs", "job search", "looking for work", "job openings", "search LinkedIn", "remote jobs", "buscar trabajo", "ofertas de trabajo", "ofertas de empleo", "empleo remoto", "vacantes", "buscar empleo", "trabajo remoto", "career opportunities", "hiring", "job listings".

ClawHub Agent Skills author: Joe v1.1.0 MIT-0 4 files · 1 script body ≈ 1 007 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

LinkedIn job search assistant that scrapes listings, filters by technologies and countries, and scores matches with AI.

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedurePeople and hiringSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

    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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (job-hunter) differs from the folder (jobclaw)
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 21 steps
    • 100Execution cost. Instruction body is 1007 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 16 example trigger phrases
    • +3Description length 534: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: suspicious
    The skill is a coherent job-search helper, but it needs Review because it stores a Gemini API key and job-search history locally in plaintext and sends user/job details to Gemini for scoring.
    LLM: suspicious (high) · VirusTotal: · 12 Sept 2026