SKILLEMALL.ai

AB resume-customizer

Tailors resumes to match specific job descriptions (JD) with multi-format support (PDF, Word, Markdown, HTML, text), ATS optimization, keyword analysis, skill matching, and industry-specific customization. Supports both Chinese and English resumes.

ClawHub Agent Skills author: Agjvsxgm v1.0.3 MIT-0 19 files body ≈ 2 600 tokens Open the sourceclawhub.ai analyzed 2 d ago

Tailors resumes to match specific job descriptions (JD) with multi-format support (PDF, Word, Markdown, HTML, text), ATS optimization, keyword analysis, skill…

As a process B 68/100 · Nearly there — weak spots: running it twice, progress reporting

ProcedureWordPDFPeople and hiringtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
B
68/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Failures and branches w 10
50
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: 19. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "agent_created"

    Process rating: all ten parameters 68/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 152 steps, 2 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2600 tokens
    • low 13 top-level sections: this looks like several domains in one skill

    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 248: enough signal without eating the budget
    • +4Structure: 39 headings
    • +3Step-by-step instructions: 152 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 5 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: suspicious
    This is mostly a resume-tailoring tool, but it needs review because it requests unrelated high-impact capability labels and can add job-description skills without verification.
    LLM: suspicious (medium) · VirusTotal: · 6 Jun 2026