AB batch-resume-screener
Batch screens multiple resumes against multiple job positions using strict evaluation rules from java-resume-screener skill. Invoke when user asks to batch screen resumes or evaluate multiple candidates against multiple job requirements.
As a process B 74/100 · Nearly there — weak spots: when it triggers, progress reporting
AnalyzerSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
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 74/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4242 tokens
- 100Tools and files. No external tools needed
- 100Steps. 52 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +3Description length 237: enough signal without eating the budget
- +4Structure: 32 headings
- +3Step-by-step instructions: 52 items
- +3Output format is stated explicitly
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.
External checks
ClawHub: suspicious
This resume-screening skill mostly does what it says, but its file handling can process more local PDFs than intended and its ZIP/data-retention safeguards are weak.
LLM: suspicious (high) · VirusTotal: · 29 May 2026