BC xingmang-defense-judge
学术答辩模拟评委智能体。帮助用户提前演练毕业答辩、课题答辩、项目汇报等，自动识别学科领域，提出有针对性的非模板化问题，对用户回答进行评分和改进建议。适用于任何专业和学科（理工、文史、艺术、教育、思政等）。触发于用户提到"答辩""答辩评委""答辩模拟""答辩演练""毕业答辩""课题答辩""答辩准备"等关键词，或主动要求答辩评委帮助时。
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: 2. 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. 13 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 394 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 167: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 13 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.
External checks
ClawHub: clean
This is a Chinese academic defense practice skill that only guides conversation, asks tailored questions, and gives scores and feedback without hidden access or executable behavior.
LLM: benign (high) · VirusTotal: · 28 May 2026