本文へ移動
cccskills
無料GitHub で公開

cowork-qbr-builder

Build a quarterly business review from a client folder -- reports, usage exports, support tickets, meeting notes, emails. Extracts delivered value with receipts, surfaces risks before the client does, and drafts the QBR narrative plus expansion asks. For agencies, consultancies, and CS teams.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md3.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Cowork QBR Builder

Prepare a QBR the way a top customer-success lead does: prove the value delivered with specifics, name the problems before the client names them, and earn the expansion conversation. Input: a folder of client artifacts for the quarter -- status reports, deliverables, usage/analytics exports, support tickets, meeting notes, email threads -- plus the engagement's stated goals if documented.

Workflow

  1. Reconstruct the quarter. From the folder, build a timeline of what actually happened: deliverables shipped (with dates), meetings held, issues raised and resolved, scope changes. Distinguish documented fact from inference.
  2. Score against goals. Map the quarter's work to the engagement's stated objectives. For each goal: status (achieved/on-track/at-risk/missed), the evidence, and the metric where one exists. If no goals were ever documented, say so -- and propose measurable ones for next quarter, because that gap is itself a finding.
  3. Mine the wins. Extract concrete value receipts: metrics that moved, hours saved, incidents prevented, quotes from the client's own emails ("this saved our launch"). Specific and cited beats impressive and vague.
  4. Face the misses. List what slipped, stalled, or disappointed -- with the honest reason and the fix already in motion. A QBR that hides the miss the client remembers loses the room.
  5. Health and risk read. From ticket sentiment, email response patterns, meeting attendance, and champion activity: engagement health (strong/stable/drifting), risks (champion departure, budget noise, declining usage), and renewal posture.
  6. Draft the QBR. Output qbr-[client]-[quarter].md structured for a deck: executive summary, goals scorecard, wins with receipts, misses with fixes, next-quarter plan, and -- only where the evidence supports it -- 1-2 expansion recommendations framed around the client's goals, not your revenue. Hand to pptx or presentation-design-enhancer for the deck build.

Rules

  • Every win cites its source artifact. Unsupported claims get cut, not softened.
  • Report the quarter that happened, not the quarter that was planned. If the folder shows drift, the QBR shows drift.
  • Client's language over your jargon: pull their vocabulary from their own emails and notes.
  • Expansion asks must trace to an observed need in the artifacts. No need observed, no ask drafted.
  • Keep confidential internal material out: internal cost notes, margin discussions, and team-performance comments in the folder never surface in client-facing output.
  • If the folder is thin (< 5 substantive artifacts), lead with the documentation gap and build what is defensible rather than padding.

Quick Commands

  • "Build the QBR from [folder]" -- full workflow
  • "Just the wins" -- step 3, receipts list
  • "Health check" -- step 5 only
  • "What should next quarter's goals be?" -- proposed measurable objectives from the evidence

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3392026年10月2日 更新

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3392026年10月2日 更新

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3392026年10月2日 更新

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3392026年10月2日 更新

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3392026年10月2日 更新

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3392026年10月2日 更新

OneWave-AI のスキルをすべて見る

このスキルの問題を報告する