AC job-interview-coaching
Use this skill to coach candidates and interviewers for job interviews: prepare truthful examples, critique interview transcripts, run interactive mock interviews and targeted practice, design structured questions and evidence-based scorecards, and improve candidate experience. Adapt to profession, seniority, and interview format. Do not use for journalism, user research, workflow discovery, general resume writing, clinical interviewing, or autonomous hiring decisions.
The skill promises interview prep for candidates and interviewers: example generation, transcript analysis, mock interviews with feedback, question design, and scoring rubrics. Adapts to profession and seniority level. Data shows 48 files, 2771 body tokens, zero critical errors. Safety score 100, quality 89 suggest solid content without red flags. Process score 59 hints at gaps in automation, but that's acceptable for interactive coaching.
The author explicitly blocks journalism, user research, and autonomous hiring—boundaries are clear. No sandbox or model runs, so real-world effectiveness of mock interviews remains untested. Runs on 10 platforms including Claude and Cursor. Worth installing if you coach people for interviews and can validate examples against your own candidate pool.
Use this skill to coach candidates and interviewers for job interviews: prepare truthful examples, critique interview transcripts, run interactive mock…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 44. 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
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 1 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 85Steps. 6 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2771 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
- +5Description has no quoted example phrases that should trigger the skill
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 473: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 6 items
- +4Reference files are cited in the instructions (36 of 36)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.