AD gpt-review
用 ChatGPT 审稿的自动化工具。通过 CDP 控制 Brave Browser 中的 ChatGPT，自动发送审稿 prompt、等待回复、提取完整响应。Use when: (1) 需要用 ChatGPT 作为次审模型审查稿件 (2) 需要获取 ChatGPT 对文章的事实核查、逻辑检查、AI痕迹检测意见 (3) 多模型互补审稿流程中需要 ChatGPT 的独立意见 (4) 用户提到"GPT审稿""ChatGPT审查""次审"。Requires: Brave Browser running with --remote-debugging-port=9222, ChatGPT logged in.
用 ChatGPT 审稿的自动化工具。通过 CDP 控制 Brave Browser 中的 ChatGPT，自动发送审稿 prompt、等待回复、提取完整响应。Use when: (1) 需要用 ChatGPT 作为次审模型审查稿件 (2) 需要获取 ChatGPT 对文章的事实核查、逻辑检查、AI痕迹检测意见…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: 用 ChatGPT 审稿的自动化工具。通过 CDP 控制 Brave Browser 中的 ChatGPT，自动发送审稿 promp… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 542 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
- -224 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 304: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.