AC auto-job-applier
Automatically find and apply to jobs that match the user's resume using the resumex.dev API, web search, and browser automation. Use this skill whenever the user asks to: search for jobs, find job matches, auto-apply to jobs, apply for jobs automatically, find jobs based on my resume, or any variant of job hunting, job searching, or job application automation. Fetches the user's full resume data from resumex.dev, extracts skills/experience/preferences, searches for matching jobs on the web, presents an approval list, then automatically fills and submits applications using browser control. Logs all applications to the user's resumex.dev job tracker. Always use this skill when the user mentions "apply to jobs", "job search", "find jobs for me", "auto apply", or "job hunting" — even if they haven't explicitly mentioned resumex.
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6320 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "requires"
Process rating: all ten parameters 57/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 7 mutating operations with no state check
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 6320 tokens
- 85Steps. 76 steps, 1 vague phrases
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 14 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 836: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +4Structure: 28 headings
- +3Step-by-step instructions: 76 items
- +4Has examples (23 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 7 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.