AD interview-prep
AI面试模拟与辅导。基于用户简历和JD生成定制化面试题库，逐题模拟面试并提供评分与示范回答。 触发词：面试模拟、面试准备、简历面试、interview prep、面试练习、 面试辅导、帮我准备面试、出面试题、面试题生成、interview practice、 mock interview、面试官模拟。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 41/100
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (interview-prep) differs from the folder (interview-prepare)
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 31 steps
- 100Execution cost. Instruction body is 578 tokens
- 100Running it twice. No mutating operations
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 151: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: clean
This is a coherent interview-prep skill, but users should be mindful that resumes, job descriptions, files, URLs, and search queries may be processed to generate coaching content.
LLM: benign (high) · VirusTotal: · 29 May 2026