SKILLEMALL.ai

AD gemini-openai-chat-export-analyze

当用户要导出并分析与 Gemini(Google)或 ChatGPT(OpenAI)网页版的全部聊天历史时,加载本 skill。典型触发:用户提到 "导出 gemini 对话"、"gemini 聊天记录"、"chatgpt 数据导出"、"OpenAI conversations.json"、"我和 gemini/chatgpt 聊过什么"、"chatgpt 历史记录" 等。注意:本 skill 覆盖 ChatGPT 网页版与 Gemini 网页版(含 gemini.google.com 和 aistudio.google.com),不包括 API 调用记录或第三方客户端。

ClawHub Agent Skills author: 少卿 v0.1.0 MIT-0 2 files body ≈ 1 449 tokens Open the sourceclawhub.ai analyzed 4 d ago

当用户要导出并分析与 Gemini(Google)或 ChatGPT(OpenAI)网页版的全部聊天历史时,加载本 skill。典型触发:用户提到 "导出 gemini 对话"、"gemini 聊天记录"、"chatgpt 数据导出"、"OpenAI conversations.json"、"我和…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 43/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1449 tokens
  • low 11 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

  • +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
  • +5Description quotes 6 example trigger phrases
  • +3Description length 289: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill gives local instructions for exporting and analyzing ChatGPT and Gemini chat histories, with privacy risks disclosed and no evidence of hidden or unsafe behavior.
LLM: benign (high) · VirusTotal: · 26 Jun 2026