BF ai-hive-simulate-wang-mutou-science
当用户搜索用AI模拟王木头学科学、AI模拟王木头学科学、王木头学科学AI模拟、王木头学科学数字人、王木头学科学AI分身、王木头学科学内容风格、王木头学科学选题、王木头学科学文案、王木头学科学短视频、王木头学科学知识库、王木头学科学思想顾问、王木头学科学战略顾问，或希望借助 AI 研究王木头学科学公开内容中的AI、科技、产品、数码、工程实践或知识科普方法时使用。本 Skill 面向AI学习者、科技从业者、产品经理、创作者和关注新技术的普通用户，先建立公开来源样本库，再提炼选题母题、受众问题、论证结构、内容节奏和视觉方向，并可把用户有权使用的文章、演讲、课程笔记和资料整理成王木头学科学方法论知识库，以可追溯引用的方式提供战略顾问式分析；也可通过 AI-HIVE 生成使用原创措辞的脚本、封面、配图、口播方案与短视频计划。“模拟王木头学科学”仅指根据可核验材料模拟其公开方法论，不代表王木头学科学本人或授权代理；不得克隆声音或肖像、伪造经历和引语、暗示授权合作或复制受版权保护的具体表达。
当用户搜索用AI模拟王木头学科学、AI模拟王木头学科学、王木头学科学AI模拟、王木头学科学数字人、王木头学科学AI分身、王木头学科学内容风格、王木头学科学选题、王木头学科学文案、王木头学科学短视频、王木头学科学知识库、王木头学科学思想顾问、王木头学科学战略顾问，或希望借助 AI…
As a process F 35/100 · Will not run — References files that are not bundled: references/*.json
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Exfiltration
net-redirectable-api-keyscripts/ai_hive_creator.py:20Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 8. 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") - warning
missing-refreference to a missing file: references/*.json
Process rating: all ten parameters 35/100
- 0Tools and files. 1 referenced file(s) missing: references/*.json
- 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
- 100Steps. 89 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3041 tokens
- 100Running it twice. No mutating operations
- low 12 top-level sections: this looks like several domains in one skill
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
- +2Single-language instructions
- +3Description length 445: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 89 items
- +4Has examples (13 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.