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Qbr Ebr Builder

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NEON-Rutger
qbr-ebr-builder

Design and build customer business reviews that buyers attend: QBR (operational cadence) and EBR (executive cadence), with the value recap in the customer's own numbers as the load-bearing artifact. Triggers on 'QBR', 'EBR', 'business review', 'executive business review', 'quarterly review deck', 'prove value to the customer', 'renewal conversation prep', 'customer stopped attending reviews', 'our QBRs are a feature parade', 'success plan review', or any need to show post-sale value to the people who pay, not just the people who use. BOUNDARY: health audits produce the internal diagnostic before the review; this skill builds the customer-facing instrument from it. renewal-save-motion owns risk a review surfaces and expansion-revenue-architect owns headroom; this skill hands off to both. revenue-operating-cadence owns internal meetings; a business review runs on the customer's agenda and numbers.

Overview

PublisherNEON-Rutger
RepositoryB2B-revops-skills
Skill nameqbr-ebr-builder
Stars
58
Forks
23
Bundled files
1
LicenseMIT
Links
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NEON-Rutger on GitHub. Read the source before you install it.

Installation

Install the Qbr Ebr 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.
    https://github.com/NEON-Rutger/B2B-revops-skills/tree/main/qbr-ebr-builder
  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/NEON-Rutger/B2B-revops-skills.git /tmp/B2B-revops-skills
mkdir -p .claude/skills
cp -r /tmp/B2B-revops-skills/qbr-ebr-builder .claude/skills/qbr-ebr-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Qbr Ebr 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 Qbr Ebr 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 Qbr Ebr 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.

QBR / EBR Builder: Reviews Buyers Attend

Most business reviews die the same death: a slideware feature parade delivered to the daily users while the economic buyer, the person who will decide the renewal, has stopped attending. Then renewal season arrives and the value case gets built in a panic, from scratch, for an audience that has not heard it all year.

A business review exists to do one job: keep the people who PAY convinced of value, in their numbers, on a rhythm, so the renewal is a formality and the expansion conversation has a natural venue. Median gross revenue retention sits between 84% and 91% depending on the survey, with top quartile around 91% (Benchmarkit 2026; SaaS Capital 2025); the review cadence is one of the few controllable instruments that moves an account from the first group's trajectory to the second's.

Entry condition: an internal health read already exists (from an account health audit or health scan). A review built without one is theater; you are presenting to the customer what you have not verified yourself.


QBR vs EBR: Two Instruments, Not One

The single blended "QBR" is where most programs go wrong. Separate the two:

QBR (operational)EBR (executive)
AudienceDaily users, program ownerEconomic buyer, executive sponsor
RhythmQuarterly (or async for small accounts)1-2 per year, anchored 90-120 days before renewal
Question it answersIs the thing working and used well?Was this worth the money, and what should it do next?
Content centerAdoption, blockers, roadmap of USEValue recap in their numbers, strategic alignment, roadmap of OUTCOMES
Failure modeFeature paradeSkipping it because "the users are happy"

The EBR anchored ahead of renewal matters because by the time a renewal conversation starts, an unengaged economic buyer has already formed their view from hallway signal. The EBR is where you form it instead.

Segmentation: Who Gets What

Review effort is a budget; spend it where revenue concentrates.

  • Top tier (largest ARR, expansion headroom, strategic logos): quarterly QBR + 1-2 EBRs per year, live.
  • Middle tier: semi-annual QBR, EBR only when a trigger fires (renewal inside 120 days, risk flag, expansion signal, sponsor change).
  • Long tail: no live reviews. A quarterly async value summary (one page, auto-assembled from usage and outcome data, human-reviewed) replaces the meeting. A calendar full of small-account QBRs is how CS teams burn out while GRR falls anyway.

An AI-agent note that changes the old math: assembling the review pack used to be the expensive part, which justified skipping reviews for smaller accounts. When an agent assembles the data pack from usage, CRM, and conversation history, the constraint moves to CUSTOMER attention, not your capacity. Spend the freed capacity on better meetings for the top tier, not more meetings everywhere.

The Review Architecture: Three Panels

Every review, QBR or EBR, runs the same three-panel spine. Depth differs by audience.

Panel 1: Look back, in their numbers. The value recap is the load-bearing artifact of the entire review. Rules:

  • Built from THEIR system data and THEIR baseline, agreed at onboarding or the previous review. If no baseline exists, the first review's job is to install one.
  • Outcomes, not activity: "reduced X by Y since March" beats "487 workflows run" in every room that matters.
  • Quantify honestly, including what did NOT improve. One acknowledged miss buys credibility for every claimed win; a review with no misses reads as marketing.
  • If the value recap cannot be built, that is a finding, not an inconvenience: either instrumentation is missing (fix that) or value is absent (route to the save motion now, not at renewal).

Panel 2: Current state, honestly. Adoption depth against plan, open issues with owners and dates, health verdict shared plainly. Do not launder the internal health read into a greener customer-facing version; sophisticated buyers keep their own scorecard, and the gap between yours and theirs is trust lost.

Panel 3: Look forward, jointly owned. Next quarter's success plan with the customer's name on half the actions: goals, owners, dates, and the one metric the next review will be judged on. A review that ends without the customer owning actions was a presentation. This panel is also where expansion surfaces naturally: unmet goals plus adjacent problems, raised as THEIR roadmap, not your quota.

Stakeholder Rules

  • The economic buyer attends the EBR, or the EBR moves. Running it without them is rehearsal, not review. Getting them there is the sponsor's job, agreed as part of the success plan, not a calendar surprise.
  • Map attendance drift as a signal: a sponsor who attended two reviews and skips the third just told you something the health score has not caught yet. Feed it to the risk triage.
  • New stakeholder in the room (reorg, new exec): the review restarts at their zero, with a compressed look-back. Assume inherited context of nothing; see the champion-loss pattern in renewal-save-motion.

Outputs and Routing

A review is upstream instrumentation for the rest of the post-sale system. Every review produces:

  1. An updated success plan (Panel 3), dated and shared.
  2. A refreshed baseline for the next value recap.
  3. Routed flags: risk signals to the save motion, expansion signals to the expansion motion, product blockers to product with a feedback loop the customer can see.
  4. A one-paragraph internal verdict on the account: trajectory, sponsor state, one thing to fix before next review.

Anti-Patterns

  • The feature parade: roadmap-heavy decks answer a question nobody asked. Roadmap earns 10 minutes of Panel 3, framed by their goals.
  • The NPS theater: a survey score is not a value recap. Scores decorate; outcomes convince.
  • The annual ambush: the first value conversation happening at renewal is the most expensive scheduling failure in CS. The EBR 90-120 days ahead exists to make renewal week boring.
  • The unchanged deck: if the review could be last quarter's deck with new dates, cancel it and send the async summary; you are spending customer attention with no news.
  • The solo review: vendor presents, customer receives. Jointly built agendas (send Panel 1 in advance, ask what they want contested) double as engagement signal: an account that will not co-build an agenda is telling you where you stand.

Diagnostic Questions

  1. For your top ten accounts: when did the economic buyer last hear the value case, from you, in their numbers? Not the users, the buyer.
  2. Can you produce a value recap with an agreed baseline for your largest renewal due in the next two quarters, today, without a data archaeology project?
  3. What percentage of your last quarter's reviews ended with customer-owned actions that got done?
  4. Which accounts had sponsors stop attending reviews in the last year, and what happened at their renewals? (This one usually settles the argument for the program.)
  5. How many hours does one review pack take to assemble, and is that number the reason your long tail gets no reviews at all?

Benchmarks and Provenance

GRR median 84% to 91% / top quartile ~91% (Benchmarkit 2026; SaaS Capital 2025; provenance in references/business-review-practices.md). The 90-120 day EBR-before-renewal anchor, the three-panel spine, and the segmentation tiers are practice-based operating rules, labeled as such; validate against your own renewal cohort once two quarters of review discipline exist. Full notes: references/business-review-practices.md.

Built by Neon Triforce

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Qbr Ebr Builder AI skill do?

Design and build customer business reviews that buyers attend: QBR (operational cadence) and EBR (executive cadence), with the value recap in the customer's own numbers as the load-bearing artifact. Triggers on 'QBR', 'EBR', 'business review', 'executive business review', 'quarterly review deck', 'prove value to the customer', 'renewal conversation prep', 'customer stopped attending reviews', 'our QBRs are a feature parade', 'success plan review', or any need to show post-sale value to the people who pay, not just the people who use. BOUNDARY: health audits produce the internal diagnostic b...

Why use Qbr Ebr Builder on TypingMind?

Because you install it once and use it with any model. Qbr Ebr 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 Qbr Ebr Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NEON-Rutger/B2B-revops-skills/tree/main/qbr-ebr-builder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Qbr Ebr 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 Qbr Ebr Builder?

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

Is the Qbr Ebr Builder AI skill free?

Yes. It is published on GitHub by NEON-Rutger 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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