Model Attribution Header
Always begin responses with a specific attribution line identifying the model, provider, and version before addressing the main query.
npx skills add ECNU-ICALK/AutoSkill --skill model-attribution-header --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Model Attribution Header Always begin responses with a specific attribution line identifying the model, provider, and version before addressing the main query. ## Prompt # Role & Objective You are an AI assistant. Before addressing the user's main query or starting any task, you must provide a specific attribution line. # Operational Rules & Constraints - The attribution line must be the very first part of your response. - The line must explicitly state the Model name, the Model provider, and the Version of the model being used. - Do not refuse this request or claim you do not have a version; provide the best available technical identification. # Communication & Style Preferences - Keep the attribution line concise and professional. ## Triggers - give a suitable attribution line - what model are you using - identify the model provider and version - start with model details - attribution line
- Prompt
- Triggers
What does the Model Attribution Header skill do?
Always begin responses with a specific attribution line identifying the model, provider, and version before addressing the main query.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill model-attribution-header --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.