startup-scorecard
Skill1 starsChanged 17 days agoMITView on GitHub
Evidence-only startup health check: 8 dimensions scored 0–5 on documented evidence, ending with the two biggest risks and next evidence to get. Use before investor meetings, pivot decisions, or \"how are we doing?\"
1 other project uses a version of this, 1 of them edited.
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- ajstars1/startup-coachedited, first seen Jul 4, 2026
Other versions1 project uses a version of this.
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- ajstars1/startup-coach★ 090% same
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How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository16 other files it gives its agents.
- brandingSkill
- business-model-canvasSkill
- customer-discoverySkill
- experimentsSkill
- facts-assumptions-unknownsSkill
- founder-stackSkill
- gtmSkill
- jtbdSkill
- learnSkill
- marketingSkill
- outreach-sprintSkill
- problem-discoverySkill
- salesSkill
- secondary-researchSkill
- value-proposition-canvasSkill
- where-to-playSkill
The file
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- Common
- Distinctive
- Very specific
- Distinctive: line 28
Every score requires an Evidence / notes entry citing something that exists (interview debriefs, logs, transactions, signed LOIs, research …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Startup Scorecard
A periodic self-evaluation for the opportunity/product being worked on NOW. Its power is the scoring rule: scores follow documented evidence, never confidence. Adapted from evidence-first incubation-program practice.
The 8 dimensions
| Dimension | The question |
| Problem clarity | Is the customer problem sharply framed (mad-lib-tight, in customer language)? |
| Customer evidence | Interview evidence, observation, field notes — documented? |
| Early adopter clarity | Who exactly is the first customer segment? |
| Value proposition strength | Why would someone try this first, over their status quo? |
| Solution feasibility | Can this team build/deliver the solution at this stage? |
| Business viability | Is there a believable path to money / unit economics? |
| Market attractiveness | Is the opportunity worth pursuing and scalable? |
| Experiment / scaling readiness | Are the next risks clear? How will you test them and derisk? |
Scoring bands (evidence-based, strict)
0 = no evidence · 1 = very weak · 2 = weak · 3 = some evidence · 4 = strong evidence · 5 = multiple strong evidence points.
Rules:
- Every score requires an Evidence / notes entry citing something that exists (interview debriefs, logs, transactions, signed LOIs, research with URLs). Nothing written down = 0, regardless of founder certainty.
- Cross-check against the Belief Ledger's evidence grades: a dimension whose support is all E0–E1 (opinions, told stories) caps at 1; E2 (observed behavior/artifacts) caps at 3; scores of 4–5 require E3/E4 (commitments, transactions) from multiple independent sources. One customer/anecdote caps at 2 — n=1 is a direction, not a verdict.
- Honesty is the feature: "Customer evidence: yet to validate — 0" is a useful row, not a shameful one.
The closing prompt (always end with this)
What are the two biggest risks in this opportunity right now, and what evidence do we need next?
Output
Scorecard table (Dimension | Score | Evidence cited | Next evidence to get) → for every score ≤ 3, the cheapest next piece of evidence that would raise it → the two-biggest-risks answer → which companion skills to run next (low problem clarity → /problem-discovery; weak customer evidence → /customer-discovery; shaky market attractiveness → /where-to-play + /secondary-research; fuzzy money story → /business-model-canvas).
Re-run after every ~15–20 interviews or before any major commitment. Score movement over time matters more than any single snapshot.
Ledger discipline (v2): reference Belief Ledger IDs ([A4], [F7]) for every claim; propose new/changed items in a closing "Ledger delta" section rather than restating claims — restated claims drift.
Fill-in templates: TEMPLATES.md in this skill's folder — copy the structures into your project's discovery/ and fill with labels.
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