Tool Design Sprint Test And Score logo

Tool Design Sprint Test And Score

Organization
product-on-purpose
tool-design-sprint-test-and-score

Day 5 (Friday) sprint-closing move of a Design Sprint that produces the bundled Friday artifact covering per-customer interview observations, best quotes, scorecard grid (sprint questions by customers), observed patterns, hot takes from each team member, and the Decider summary (build, iterate, pivot, or stop, plus highest-confidence learning, most important revision, and next artifact). Use Friday after Thursday's prototype passes trial run and during/after the 5 customer interviews. The sprint's payoff artifact.

Overview

Publisherproduct-on-purpose
Repositorypm-skills
Skill nametool-design-sprint-test-and-score
Stars
717
Forks
92
Bundled files
3
LicenseApache-2.0
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.

  • 3 bundled files

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

  • Open source

    Published by product-on-purpose on GitHub. Read the source before you install it.

Installation

Install the Tool Design Sprint Test And Score 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/product-on-purpose/pm-skills/tree/main/skills/tool-design-sprint-test-and-score
  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/product-on-purpose/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/skills/tool-design-sprint-test-and-score .claude/skills/tool-design-sprint-test-and-score
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tool Design Sprint Test And Score 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 Tool Design Sprint Test And Score 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 Tool Design Sprint Test And Score 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.

Design Sprint Test and Score (Friday)

Friday is the sprint's payoff. 5 target-profile customers run the prototype while the team observes; the team synthesizes observations into a scorecard against the sprint questions; the Decider makes the build / iterate / pivot / stop call by end-of-day. The week's 35-40 person-days plus customer recruiting cost converts into one actionable decision.

Family contract: docs/reference/skill-families/design-sprint-skills-contract.md. This skill is a member of design-sprint-skills.

When to Use

  • It is Day 5 of the Design Sprint and Thursday's prototype passed trial run.
  • 5 confirmed participants are scheduled (canonical; or 4 if 1 cancelled-and-no-buffer; pause if below 4).
  • The team can observe interviews live (in-person or via Zoom breakout room) and synthesize during the day.
  • The Decider is present Friday PM for the post-interview review (canonically 14:00-18:00 PT window covering observation of slots 4-5 plus Decider review by 17:30 PT).

When NOT to Use

  • Thursday prototype did not pass trial run. Re-run trial; if still failing at 19:00 PT Thursday, postpone Friday.
  • Fewer than 3 customers confirmed. Per Ratified Decision 3, the canonical guidance is 5 customers; 3-4 or 6-7 gets a documented warning; below 3 or above 7 should trigger a re-decision (postpone or split testing). Note: the v0.1.0 family validator does NOT mechanically enforce these thresholds (cohort count is in the EXAMPLE artifact, not in frontmatter); enforcement is a v2.16 validator-expansion candidate.
  • Decider unavailable for the post-interview review window. Without Decider, the day produces observations without a call.
  • The team plans to use this skill to write the executive memo. Per Ratified Decision 4: exec memo authoring is delegated to foundation-stakeholder-update (existing pm-skills foundation skill); this skill produces the Decider summary only.

What This Skill Produces

A single bundled artifact with six sections:

  1. Per-customer interview observation notes: one section per customer; covers Context (Act 2) reactions, Tasks (Act 4) behavior with timestamps, Debrief (Act 5) reactions including pricing. Captured live during the day's interviews.
  2. Best quotes: 5-15 verbatim customer quotes the team flags as most signal-bearing. Used in the Decider summary and in any downstream pitch or planning artifact.
  3. Scorecard grid: rows are the sprint questions (from Monday); columns are the 5 customers; each cell is Y / N / partial / unclear with a one-line note; rightmost column is the team's day-end decision per question (Validated / Invalidated / Inconclusive).
  4. Observed patterns: 4 buckets (worked, hesitated, broke trust, unexpected) with 2-4 patterns per bucket. Each pattern names how many customers showed it.
  5. Hot takes: one short paragraph per team member capturing their personal read on Friday before group synthesis biases the read. Written silently in parallel.
  6. Decider summary: the Decider's call (build / iterate / pivot / stop / reframe) plus the highest-confidence learning, the most important revision the team would make to the prototype direction, and the next artifact the team will produce (the post-sprint deliverable).

See references/TEMPLATE.md for the canonical structure and references/EXAMPLE.md for the Brainshelf book-catalog Friday artifact.

Friday Time Structure

Friday is the longest day: customer interviews start early (canonically 09:00 PT) and the Decider review concludes the day (canonically 17:30 PT).

  • 09:00-16:30: 5 customer interviews of 50-60 minutes each at 09:00 / 10:30 / 12:00 / 14:00 / 15:30. Each slot: 10 min setup + 50-55 min interview + 5 min team huddle to capture observations before next customer.
  • 13:00-14:00: Lunch (slot 3 wraps ~13:00; lunch overlaps the slot 3 to slot 4 buffer)
  • 16:30-16:45: Last-customer wrap; observation note tidy
  • 16:45-17:00: Team writes hot takes silently in parallel
  • 17:00-17:30: Decider reviews scorecard + hot takes; makes the call
  • 17:30-18:00: Decider summary captured; team begins post-sprint disposition (next-step calendar, downstream deliverable assignment)

This skill's 270-minute timebox covers the synthesis sections (scorecard, patterns, hot takes, Decider summary). The 5 interviews themselves (~5 hours of interview time) run in parallel with continuous observation capture.

Scorecard Mechanic

The scorecard is a 2-D grid. Rows are sprint questions from Monday's map-and-target (typically 3-7). Columns are the 5 customers (anonymized IDs). Each cell answers: did this customer's interview validate, invalidate, or leave inconclusive the row's question?

C1C2C3C4C5Day-end decision
Q1YYNYpartialValidated (4 of 5)
Q2NYunclearNNInvalidated (3-of-5 N, 1 of 5 Y)
.....................

Day-end decision rules:

  • Validated: 4 or 5 of 5 Y (strong signal); 3 of 5 Y with no N (directional). For 4-customer cohorts: 4 Y is Validated; 3 Y with no N is directional.
  • Invalidated: 4 or 5 of 5 N. For 4-customer cohorts: 4 N is Invalidated; 3 N with no Y is directional.
  • Inconclusive: all other patterns. Inconclusive questions get scheduled for follow-up (a smaller test, a quant experiment, or a second Design Sprint).

The Decider can override day-end decisions but should record reasoning.

Common Pitfalls

  • Observation notes too narrative, not behavioral. "Customer seemed confused" is a narrative; "Customer hovered on the capture button for 4 seconds without tapping, then tapped twice in rapid succession" is behavior. Behavior is data; narrative is interpretation.
  • Scorecard cells filled in by consensus. Each observer writes their cell read; differences are surfaced, not averaged. If C1's read on Q1 is split 2 Y vs 2 N across the team, the cell is "split" with an explanatory note.
  • Hot takes written after group synthesis. Hot takes are written SILENTLY and in PARALLEL before group synthesis. Writing them after a group debrief produces consensus, not signal.
  • Decider hesitating on the call because "we want more data." Friday's job is to produce a call with the data you have. If the call truly cannot be made, the call is "iterate" (re-sprint with adjustments). "Defer" is not an answer.
  • Skipping the Decider summary because "we'll write it up Monday." The summary is captured Friday before the team leaves. Monday is too late; context decays fast.
  • Treating "5 customers" as a soft target. Per the canonical research, 5 is where confidence about patterns crosses an inflection point. Fewer than 4 produces noisy signal; more than 7 produces synthesis-overload without much marginal signal.

Cross-Skill Usage

Prerequisites: tool-design-sprint-prototype-plan. Friday consumes the prototype and the interview script from Thursday. Without a working prototype that passed trial run, Friday cannot run.

This skill does NOT invoke tool-note-and-vote. Friday has no voting moment; the scorecard cells are individual reads and the Decider summary is the Decider's call.

This skill does NOT author an executive memo (per Ratified Decision 4). If the team wants an exec memo or stakeholder update, the next invocation is foundation-stakeholder-update, which consumes the Decider summary as input.

Downstream invocations after the sprint closes: deliver-prd (if Decider call is "build"); measure-experiment-design (if "iterate" requires a smaller follow-on experiment); iterate-pivot-decision (if "pivot" requires documenting the pivot rationale); foundation-stakeholder-update (if any of the above need stakeholder communication).

Canonical Sources

Decider Checkpoint

This skill ends with a Decider Checkpoint in references/TEMPLATE.md. The Decider's call (build / iterate / pivot / stop / reframe) IS the checkpoint; the sprint cannot close without it. The checkpoint also captures the next artifact the team owns producing (a PRD, a smaller experiment, a pivot memo, or a stakeholder update), which is what triggers Monday's post-sprint work to begin clean.

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 Tool Design Sprint Test And Score AI skill do?

Day 5 (Friday) sprint-closing move of a Design Sprint that produces the bundled Friday artifact covering per-customer interview observations, best quotes, scorecard grid (sprint questions by customers), observed patterns, hot takes from each team member, and the Decider summary (build, iterate, pivot, or stop, plus highest-confidence learning, most important revision, and next artifact). Use Friday after Thursday's prototype passes trial run and during/after the 5 customer interviews. The sprint's payoff artifact.

Why use Tool Design Sprint Test And Score on TypingMind?

Because you install it once and use it with any model. Tool Design Sprint Test And Score 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 Tool Design Sprint Test And Score in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/product-on-purpose/pm-skills/tree/main/skills/tool-design-sprint-test-and-score. 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 Tool Design Sprint Test And Score?

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 Tool Design Sprint Test And Score?

As many as you like. As long as a model supports skills, you can use Tool Design Sprint Test And Score with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tool Design Sprint Test And Score AI skill free?

Yes. It is published on GitHub by product-on-purpose under the Apache-2.0 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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