SKILLEMALL.ai

AC job-search-tailor

Daily job search + resume archetype matching skill. Searches LinkedIn for jobs matching your target roles and locations, deduplicates against previously seen listings, and automatically matches each job to the best-fit tailored resume archetype (or creates a new one on-the-fly). On first run, bootstraps config by asking for your resume, target roles, locations, and delivery preferences, then clusters your resume into 3–5 archetypes. Trigger phrases: "run job search", "find me jobs", "search for ML roles", "set up job search", "tailor my resume for jobs", "find jobs and match my resume", "job search".

ClawHub Agent Skills author: ericshi123 v0.1.1 MIT-0 9 files body ≈ 1 733 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructuretype 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
59/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Inputs and preconditions w 11
30
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: 8. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 9 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 42 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1733 tokens
    • 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 7 example trigger phrases
    • +3Description length 607: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 42 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 3 scripts are documented

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

    External checks

    ClawHub: clean
    This skill does what it says: it searches jobs, tailors resumes, and stores job-search state locally, but users should understand that resume-derived files persist on disk.
    LLM: benign (high) · VirusTotal: · 29 May 2026