القائمة
Generate 5 engaging tweet options based on a topic or description
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | tweet |
| description | Generate 5 engaging tweet options based on a topic or description |
| user-invocable | true |
| argument-hint | [topic or description] |
Generate 5 engaging and exciting tweet options based on the user's description. Each tweet must:
wc -c to verify character count for each tweetFormat your response as:
Ensure all tweets meet the character limit before displaying.
Note: Display the tweet options in chat only. Do not write to any file.
Ship a completed feature - lint, test, commit, push, PR, subagent review loop, risk-rated PR description. Use when the user says "finish this feature", "ship it", "wrap this up", or "create the PR".
Ask the user a few casual clarifying questions before acting. Reliable trigger is the explicit /questions command. Soft trigger is the message's last character being a question mark, but that's a phrase-match heuristic the model may miss - use /questions when you want it guaranteed. Lighter, more conversational sibling of "grill me" style interviews - not relentless, just a couple of genuine questions to sharpen the request before doing work.
Update a project's documentation to reflect code changes on the current branch before opening a PR. Use when the user finishes a feature/fix and is about to create a PR, or asks to "sync docs", "update the docs for these changes", or check whether documentation needs updating.
Give an honest opinion without implementing anything, when a user message ends with "wdyt", "wdyt?", or "what do you think" (also "what do you think?"). Use this instead of jumping to a plan or code. Surfaces concerns, tradeoffs, and clarifying questions, then waits for the user's response before doing any work.
Route subtasks to other models - glm-5.2 (opencode), gpt (codex exec), grok-4.5 (grok build), Claude subagents - with cost/quality routing and verification. Use when the user says "delegate", "farm this out", "have glm/codex/grok do it", or asks to split a task across models. Not for ordinary tasks the main agent should do itself.
Multi-model code review - the /review methodology with finder agents routed to cheap models on other harnesses (gpt via codex, glm via opencode) through the delegate skill, verified and synthesized by the main agent. Use when the user says "delegate-review", "multi-model review", or "review this PR with cheap workers".