AD job-auto-apply
Automated job search and application system for Clawdbot. Use when the user wants to search for jobs and automatically apply to positions matching their criteria. Handles job searching across LinkedIn, Indeed, Glassdoor, ZipRecruiter, and Wellfound, generates tailored cover letters via SkillBoss API Hub, analyzes job compatibility with AI, fills application forms, and tracks application status. Use when user says things like "find and apply to jobs", "auto-apply for [job title]", "search for [position] jobs and apply", or "help me apply to multiple jobs automatically".
As a process D 45/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
The same skill appears in 1 more place: ClawHub
How to improve
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "requires_env"
Process rating: all ten parameters 45/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (job-auto-apply) differs from the folder (qui-job-auto-apply)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 47 steps
- 100Execution cost. Instruction body is 1649 tokens
- 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
- +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 4 example trigger phrases
- +3Description length 575: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.