Day 2 end capstone move of a Foundation Sprint. Compresses the sprint's full strategic frame into a single canonical sentence (the Founding Hypothesis) plus an assumption scorecard, why-we-believe, what-could-prove-us-wrong, and recommended next validation step. Use after Magic Lenses is signed. Strict canonical template; paraphrase is not accepted in v0.1.0. The Founding Hypothesis is the spine artifact the sprint exists to produce.
npx skills add https://github.com/product-on-purpose/pm-skills --skill tool-foundation-sprint-founding-hypothesis
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
Day 2 end of a Foundation Sprint. The team compresses the full sprint output into a single canonical sentence plus a testable scorecard. This is the artifact the sprint exists to produce; everything before this skill was preparation. Without a ratifiable Founding Hypothesis, the sprint failed.
Family contract: docs/reference/skill-families/foundation-sprint-skills-contract.md. This skill is a member of foundation-sprint-skills.
A single bundled artifact with five sections:
See references/TEMPLATE.md for the canonical template and references/EXAMPLE.md for the Brainshelf example.
If we help [target customer] solve [important problem]
with [approach], they will choose it over [competitors or alternatives]
because our solution is [differentiators].
This template is strict for v0.1.0 (per ratified spec decision). Paraphrase is not accepted. Variations like "Because we help X with Y..." or compressing two slots into one ("solve [problem] with [approach]") are rejected by the skill. The strictness is intentional: forcing the template forces the team to fill every slot specifically.
The five slots are:
| Slot | Source | Discipline check |
|---|---|---|
| target customer | Basics target customer statement | Must be specific (markers, not segments) |
| important problem | Basics important problem statement | Must be painful enough to drive switching |
| approach | Magic Lenses top bet | Must be the top bet, not a softened version |
| competitors or alternatives | Basics competitor map | Must include "do nothing" if it was named there |
| differentiators | Differentiation chosen two | Must be both differentiators, not just one |
If any slot is vague, the skill rejects the hypothesis and prompts for revision.
| Quality | What it means |
|---|---|
| Specific | Names a real customer and a real problem; not "users" and "frustrations" |
| Comparative | Explains what customers choose today, including doing nothing |
| Differentiated | States why this solution should win, not just that it should |
| Testable | Translates into scorecard questions and experiments |
| Simple | A customer can understand the promise quickly |
| Uncomfortable enough to be useful | If nobody disagrees or feels exposed, the hypothesis may be too vague |
The "uncomfortable" quality is the hardest to enforce: teams unconsciously soften the hypothesis to make it ratifiable. The skill counter-acts by asking, in the discussion phase, "Who in this room would push back on this if they weren't on this team?" Silence is a signal that the hypothesis is too safe.
Decompose the hypothesis into 5-7 assumptions (recommended; 3-10 accepted per ratified spec decision). For each:
| Field | What goes here |
|---|---|
| Assumption | One sentence, derived from a specific slot of the hypothesis |
| Why it matters | What would be invalidated if this assumption is wrong |
| Current confidence | High / Medium-high / Medium / Medium-low / Low |
| Best next test | Specific test that would change the confidence level |
The highest-risk assumption (lowest current confidence, highest blast-radius-if-wrong) is the assumption the next validation step (often a Design Sprint) should test first.
The Decider drafts the canonical sentence by filling the 5 slots from prior sprint outputs. The team reviews, identifies vagueness, and revises until each slot is specific. This is the most important 15 minutes of the sprint.
Decompose the hypothesis into 5-7 assumptions. Score each. Identify the highest-risk one.
Bulleted lists, 3-5 each. The team writes both in parallel; the second list (proof-of-wrong) is the test of whether the team is holding the hypothesis with calibration.
The Decider names the next validation step: Design Sprint, customer research, experiment, etc. The recommended test should attack the highest-risk assumption from the scorecard.
The Decider signs. The sprint ends.
The Decider's job during Founding Hypothesis:
Prerequisites: tool-foundation-sprint-magic-lenses. The top bet, backup, and decision rationale are the load-bearing inputs.
The skill inherits the Basics bundled artifact (target customer, important problem, competitors) and the Differentiation bundled artifact (chosen differentiators). All five hypothesis slots are derived from prior sprint outputs.
Next invocation outside the sprint: the recommended next validation step. Most commonly tool-design-sprint-readiness if a Design Sprint is the next test. Sometimes pm-skills:measure-experiment-design or pm-skills:discover-interview-synthesis if a non-sprint test is the right next move.
There is no formal bridge skill between Foundation Sprint and Design Sprint; the transition is narrative content in _workflows/foundation-to-design.md and in both user guides.
This skill ends with a Decider Checkpoint in references/TEMPLATE.md. The Decider ratifies the hypothesis sentence, the scorecard, and the recommended next test. Ratification closes the Foundation Sprint. Without ratification, the sprint output is incomplete and the team did not produce what it set out to produce.
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take product-on-purpose/tool-foundation-sprint-founding-hypothesis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.