pivot-decision
Skill2 starsChanged 5 months agoApache-2.0View on GitHub
Use when a founder has run real experiments and must decide whether to keep going, change direction, or stop - the moment validation results, retention, pipeline, or runway are forcing a call. Reach for this when they say "should I pivot", "is this working", "do I keep going", "should I kill it", "the numbers are flat", "I'm not sure this is it", or after validate-idea, a launch, or a metrics review returns a weak signal. Produces an evidence summary, a persevere/pivot/kill recommendation that names which kind of pivot the evidence supports, and a written decision with a tripwire date to revisit. Invoke after validate-idea, north-star-metrics, or a launch; pair with apply-mental-models and capture-learning.
In this repository25 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .cursor/rules/founderos.mdcCursor rule
- apply-mental-modelsSkill
- brand-and-namingSkill
- capture-learningSkill
- cofounder-and-equitySkill
- consumer-product-testingSkill
- customer-interviewsSkill
- find-first-customersSkill
- first-hireSkill
- founderos-prompt-scaffoldSkill
- investor-pipelineSkill
- landing-page-copySkill
- launch-planSkill
- legal-and-incorporationSkill
- north-star-metricsSkill
- pitch-deckSkill
- positioning-and-gtmSkill
- pricing-strategySkill
- runway-and-unit-economicsSkill
- scope-mvpSkill
- sensory-testingSkill
- start-hereSkill
- validate-ideaSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 26
Before any decision, gather the real signals and separate what people did from what they
- Distinctive: line 60
Write down the call, the single thing that changes, the new pass/fail bar, and a tripwire date to revisit it.
- Very specific: line 68
Next: run capture-learning to log the call and its outcome.
≈ “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
Make the Pivot Call
The hardest founder decision is not what to build, it is whether to keep going. Sunk cost, hope, and a few flattering data points keep dead ideas alive for months past the evidence, and they keep working ideas getting abandoned over one bad week. This skill turns "I'm not sure this is working" into a defensible persevere, pivot, or kill, grounded in what you actually measured, not what you wish were true.
The method
Built on the Founder OS scaffold (High tier). Full frameworks in references/pivot-playbook.md. This skill covers the whole persevere/pivot/kill call on one shared evidence base.
Step 1 - Lay out the evidence, cold
Before any decision, gather the real signals and separate what people did from what they said. Stated enthusiasm is not evidence; behaviour is.
| Signal | What it actually shows | Strong / weak / missing |
| Retention / repeat use | Whether the value is real and recurring | |
| Pipeline / conversion | Whether buyers move, not just nod | |
| Revenue / pre-payment | Whether anyone pays, not just praises | |
| Runway | How many more swings you have |
Step 2 - Score against the bar you set before you were attached
You committed to pass/fail bars in validate-idea and north-star-metrics. Hold the evidence
against those, not a goalpost you just moved. The question is never "could this work" (anything
could), it is "is it working, on the bar I set before I had feelings about it."
Step 3 - Name the call, and which kind of pivot
Decide persevere, pivot, or kill. If pivot, name which one the evidence supports (Eric Ries's taxonomy), because "pivot" without a type is just "try something else."
| The failing signal | The pivot it points to |
| Right problem, wrong slice of users | Customer-segment pivot |
| They want one feature, not the whole thing | Zoom-in pivot |
| Your thing is a feature of a bigger need | Zoom-out pivot |
| Real problem, wrong solution shape | Problem/solution pivot |
| Value lands, but you cannot reach them affordably | Channel pivot |
A real pivot keeps what is validated and changes one thing. Changing everything is not a pivot,
it is a new idea: treat it as one and run validate-idea again.
Step 4 - Write the decision and the tripwire
Write down the call, the single thing that changes, the new pass/fail bar, and a tripwire date to revisit it. A decision with no review date is a hope.
Output
- Evidence summary: did versus said, scored against your pre-set bars.
- A persevere / pivot / kill recommendation, naming the pivot type if any, with the reason.
- A written decision: the one change, the new bar, and a tripwire date to revisit.
- Next: run
capture-learningto log the call and its outcome;scope-mvporvalidate-ideaif you pivoted.
Constraints
- Judge against the bar you set before you were attached, not one you just moved to fit the result.
- Separate did from said. Enthusiasm is not retention; a warm call is not a pre-order.
- A pivot keeps what is validated and changes one thing. Do not smuggle a full restart in as a "pivot."
- This is decision support, not the decision. The founder owns the call, and an irreversible shut-down deserves a second human (a mentor or co-founder). Add the not-financial-advice caveat when runway or money is in play.
- Stay theme-agnostic; the founder supplies the domain, you supply the rigour.
Copy-paste version
Act as a sharp, kind startup coach helping a first-time founder make an honest persevere/pivot/kill
decision. Do not cheerlead and do not doom; hold me to the evidence.
My idea: [ONE_LINER]. Who it's for: [ICP]. What I bet would happen: [RISKIEST_ASSUMPTION].
What I actually measured (be specific - usage, retention, pipeline, revenue, runway): [METRIC].
The pass/fail bar I set before running it: [the number].
1. Sort my evidence into what customers DID versus what they SAID, and mark each signal strong, weak,
or missing. Hold it against the bar I set, not a new one.
2. Tell me the honest call: persevere, pivot, or kill, with the reason. If pivot, name which kind
(zoom-in, zoom-out, customer-segment, problem, channel) the evidence actually supports, and what
to keep versus change. Warn me if I'm really proposing a restart dressed up as a pivot.
3. Write my decision: the one thing that changes, the new pass/fail bar, and a tripwire date to
revisit it.
Don't let me rationalise a dead idea with a few flattering data points, and don't let me quit a
working one over one bad week.Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

