Cowork Qbr Builder logo

Cowork Qbr Builder

Organization
OneWave-AI
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.

Overview

PublisherOneWave-AI
Repositoryclaude-skills
Skill namecowork-qbr-builder
Stars
293
Forks
49
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Cowork Qbr Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/cowork-qbr-builder .claude/skills/cowork-qbr-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cowork Qbr Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cowork Qbr Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cowork Qbr Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Frequently asked questions

What does the Cowork Qbr Builder AI skill do?

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.

Why use Cowork Qbr Builder on TypingMind?

Because you install it once and use it with any model. Cowork Qbr Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cowork Qbr Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/cowork-qbr-builder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cowork Qbr Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cowork Qbr Builder?

As many as you like. As long as a model supports skills, you can use Cowork Qbr Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cowork Qbr Builder AI skill free?

Yes. It is published on GitHub by OneWave-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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