Grok Bot 的 32 个技能清单，含 Jev 段落过滤与类型化决策

Solomon Rojie @Solomonrojie原推发布于 2026.10.28

在 X 上打开原推

if you’re using Grok Bot, stop teaching it the same jobs from scratch here are 32 skills that give it a process before you give it the task shared memory, cleaner handoffs, sales workflows, and fewer wasted runs. adapt these GitHub playbooks into Grok Bot skills and connect the tools they need MEMORY & RESEARCH memory-systems → Design memory that survives between sessions. filesystem-context → Keep research in files, retrieve what matters. context-compression → Shorten history without losing key decisions. defuddle → Strip clutter from articles before reading. huggingface-papers → Find papers and their supporting resources. jev-passage-filter → Rank retrieved passages before deeper reading. TEAM & HANDOFFS grok-bot-delegation → Define the job, boundaries, and finished result. multi-agent-patterns → Choose how specialists coordinate their work. long-horizon-prompting → Give background tasks clear success and stopping rules. tool-design → Define reliable inputs, outputs, and tool errors. writing-for-agents → Write instructions agents can follow consistently. jev-typed-decision → Structure small routing and classification decisions. SALES & GROWTH customer-research → Turn customer evidence into specific needs. competitor-profiling → Investigate competitors from their websites. sales-enablement → Prepare pitches and objection-handling documents. revops → Define lead scoring, routing, and handoffs. churn-prevention → Build cancellation and payment-recovery workflows. copywriting → Turn the offer into landing-page copy. cold-email → Draft relevant outreach and follow-ups. AUTOMATION & COSTS routine-healthcheck → Flag duplicate, noisy, or overactive routines. transcript-healthcheck → Find repeated corrections worth fixing. jev-search-loop → Decide what to read before searching again. jev-watch-run → Assess whether a background job needs intervention. n8n-error-handling → Make failed automations visible and recoverable. n8n-workflow-patterns → Build around established automation patterns. n8n-validation-expert → Diagnose workflow configuration errors. QUALITY & TOKEN CONTROL evaluation → Define checks for acceptable results. advanced-evaluation → Compare outputs against a scoring rubric. context-optimization → Plan smaller, more relevant working context. context-degradation → Diagnose why long sessions lose accuracy. webapp-testing → Verify browser behavior with Playwright. skill-creator → Test and improve reusable instructions. don’t give every bot all 32 choose one recurring job. give its owner the relevant skills, required access, and a clear acceptance check run it on a real case. keep the useful steps, correct the weak ones, and save the process before scheduling it save this. your next bot should inherit a working method instead of another wall of instructions the article below explains 7 workflow changes that keep this system cheaper to run through reusable research, smaller context, and fewer failed retries ↓

这条是引用着另一条写的：x.com/i/web/status/2112214741103825314