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Found 12 Skills
For use when students **have completed WG-12 to WG-21** (single-file consolidation blueprint) and are working on **WG-22 Code Splitting** (`agent_core.py` + `main.py`). **First message in a new session**: Display PEAS brand screen and confirm readiness first; after confirmation, **lay out the context** before proceeding to requirement clarification. If **`prompts/` or `templates/`** are missing, copy them from `references/project_assets/` to the project root. Process: Spec Alignment (2d′) → Six-column Contract → **In-session Handoff Implementation** → Acceptance. Starting point: starter_main_wg21.py; Standard reference: reference_agent_core.py + reference_main.py. Triggers: peas-workshop-advanced-coach, PEAS workshop advanced coach, WG-22, code splitting coach, Agent.chat.
Siro platform help — AI field sales coaching via mobile recording, real-time Halftime mid-call coaching, automated CRM data capture, conversation analytics, follow-up draft generation. Use when setting up Siro for a field sales team, configuring Siro CRM integration with Salesforce or HubSpot via Merge, Siro recording quality or battery drain issues on job sites, building a custom integration with Siro's REST API and webhooks, comparing Siro vs Rilla vs SalesAsk for field sales coaching, or Siro coaching prompts feel too generic for your vertical. Do NOT use for virtual/video meeting note-taking (use /sales-note-taker) or building a coaching program (use /sales-coaching).
Context window coach. Proactive guidance for token-efficient Claude Code projects, multi-agent systems, and skill architecture.
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
Multi-turn conversational AI for intent extraction, clarification, and generation readiness detection. Guides users through articulating creative intent with structured parameter extraction.
Momentum platform help — AI revenue orchestration with automated CRM updates, Slack Deal Rooms, MEDDIC Autopilot, AI coaching, churn signals, and executive briefs. Use when Salesforce fields never get updated after calls, deal rooms in Slack are noisy or disorganized, MEDDIC tracking is inconsistent across reps, post-call action items aren't making it into the CRM, you need churn risk signals from customer conversations, or AI coaching scores don't match what you see on calls. Do NOT use for building outbound sequences (use /sales-cadence) or picking an AI note-taker (use /sales-note-taker).
Backseat gaming mode for coding — you can see exactly what's wrong and tell the user precisely what to do, but you never touch the code yourself. The user implements everything. Persistent, no exit. Activate with /backseat. Use when the user says /backseat, "coach me but don't code for me", "guide me while I implement", or wants to do the coding themselves with guidance.
Independent public speaking training for workplace learners. Core differentiator: Structural design driven by in-depth audience analysis. Two modes: Coach Mode (build from scratch) and Quick Mode (directly generate framework and fine-tune when materials are available). Trigger words: speech training, public speaking training, practice speaking, speech training.
Implement AI Coaching best practices on AnalyticDB for PostgreSQL (ADBPG): Leverage Supabase projects (training data management) + ADBPG instances with vector optimization to build RAG-driven coaching systems that guide users through domain-specific workflows, decision-making, or skill development. Use when: User wants to create Supabase projects (spb-xxx), ADBPG instances (gp-xxx), vector knowledge bases, or RAG-driven coaching systems on ADBPG. Triggers: "Supabase", "ADBPG", "vector database", "knowledge base", "RAG", "AI coaching", "coaching system", "spb-xxx", "gp-xxx"
Invoke when the user wants to practice English. Corrects grammar, spelling, and expression in every response. Adapts to the user's level over time. Not for code reviews or technical docs.
Barry learner English listening-and-speaking proficiency assessment + bottleneck diagnosis. In 10–17 minutes, it produces three CEFR levels for speaking, listening, and overall proficiency, pinpoints listening/speaking bottlenecks, and writes the results to Learner Profile Section 2 + 3. All learners follow one unified workflow: standardised-test inquiry (reference anchor) → Chinese-to-English progression system (starting at B1, level up on a pass, level down on a fail, assess speaking CEFR + final pronunciation question) → five-item ladder listening assessment (listening CEFR) + stage a/b bottleneck diagnosis → overall placement → confidence check + profile writing. For Chinese-to-English, "conveying the meaning clearly" is the basic pass standard; complex sentence structures and advanced vocabulary are a plus. A learner's first run is initiated by barry-onboarding; returning learners may invoke it proactively for reassessment. Trigger words: assessment, English proficiency assessment, diagnosis, English assessment, CEFR, bottleneck.
Independent translation-technique training for workplace learners. Two modes: Coach mode (Filtering → Deverbalization → Logic Surfacing → Re-expression → Cultural Adaptation, with the coach guiding each step) and Quick mode (the AI produces the translation directly, then explains step by step what adjustments were made and why). The Deverbalization stage adapts to the learner’s proficiency: the higher the proficiency, the less deverbalization is required. Trigger phrases: “translation technique training,” “translation training,” “translation practice,” “translation training.”