AC interview-assistant-skill
基于腾讯会议(tmeet)通讯录与会议录制/纪要，覆盖面试全链路——会前生成候选人画像与结构化面试提纲，会中记录关键信息，会后输出带维度评分与录用建议的结构化评估。当用户说"准备面试""生成面试提纲""面试评估""候选人画像""面试记录整理"时触发。
基于腾讯会议(tmeet)通讯录与会议录制/纪要，覆盖面试全链路——会前生成候选人画像与结构化面试提纲，会中记录关键信息，会后输出带维度评分与录用建议的结构化评估。当用户说"准备面试""生成面试提纲""面试评估""候选人画像""面试记录整理"时触发。
As a process C 53/100 · Has gaps — 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: 9. 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 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 20 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 383 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 125: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 20 items
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.
External checks
ClawHub: clean
This skill is a disclosed interview-assistance workflow that uses Tencent Meeting data or local files to prepare and evaluate interviews, with no evidence of hidden exfiltration, destructive behavior, or deceptive execution.
LLM: benign (high) · VirusTotal: · 21 Jul 2026