القائمة
Rubric for giving honest, specific, voice-aware feedback on the user's draft emails
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
Use when the user wants to build a Google ADK agent — scaffolding a new agent, adding tools/skills/prompts to one, or asking how to structure an ADK project. Triggers on phrases like "create an ADK agent", "build a Google agent", "scaffold an agent", "make an agent that does X", "I need an ADK skeleton", or any task involving generated-agents/, LlmAgent, SkillToolset, or the ADK framework. Also use whenever the user mentions `nuvel`, the `nuvel` CLI, or asks about agent architecture patterns / callbacks / HITL / streaming / ADK prompt engineering — nuvel ships the canonical knowledge skills for those topics. Lean toward triggering — if the task touches Google ADK at all, this skill is in scope.
Delegate work to sub-agents with the ADK 2.0 Task API — `mode='task'`, `mode='single_turn'`, `mode='chat'` on `LlmAgent`, the auto-attached `finish_task` tool, and typed contracts via `input_schema` / `output_schema`. Load this skill when one agent needs to hand a bounded unit of work to another and get a validated result back, or when migrating off SequentialAgent / ParallelAgent / LoopAgent.
Creating valid SKILL.md files following the agentskills.io specification — frontmatter, instructions, references directory, progressive disclosure (L1/L2/L3), and SkillToolset wiring in agent.py. Load this skill when generating domain skills for an agent.
Build graph-based agents with ADK 2.0 `Workflow` — declare nodes and edges, route conditionally, fan-out/fan-in in parallel, run dynamic nodes at runtime, and add human-in-the-loop revision cycles. Load this skill whenever the agent needs anything beyond a strictly linear or trivially parallel pipeline.
Agent architecture patterns for Google ADK 2.0 — when to reach for a single LlmAgent, a Workflow graph (new default for multi-step orchestration), or the shortcut classes SequentialAgent / LoopAgent / ParallelAgent. Load this skill when deciding the agent's top-level shape.
Pattern for turning a brief into a coherent deck outline — intent detection, section ratios, draft headings, expansion
| name | email-coaching |
| description | Rubric for giving honest, specific, voice-aware feedback on the user's draft emails |
| when_to_use | The user asks for feedback, review, critique, or "make this better" on a draft they're composing. Also fires when they paste a draft and ask "thoughts?" |
Coaching = grounded, specific, short, voice-aware. Generic advice ("be clearer", "more concise") is worse than silence.
Before saying anything about a draft, always:
get_current_compose — read the actual draft. Never coach from memory or assumption.analyze_draft — get objective metrics (word count, hedge count, passive count, opener/sign-off, longest sentence).recall_writing_style — load the user's voice rules.If recall_writing_style returns {"status": "empty"}, say so explicitly: "I haven't learned your style yet — feedback will be generic until you send a few." Then coach only on the objective metrics; skip voice claims.
For each draft, walk these in order and stop when you have 2-3 concrete points:
recall_writing_style. Call out one specific drift, not "tone feels off".hedge_count ≥ 3 in a short email is usually weakness. Quote the hedges. Suggest the assertive rewrite.longest_sentence_words from the analyzer tells you which.apology_count ≥ 2 usually means the user is over-apologizing. Replace with a direct statement of what changed.has_opener / has_signoff mismatches the user's usual pattern (per style memory).