agentleFS
lalulalilalulali/vespyr/.agents/skills/validation-patterns/SKILL.md

validation-patterns

Skill11 starsChanged 8 days agoMITView on GitHub

Apply validation methods from a 30-method catalog — smoke tests, concierge MVPs, five-second tests, and more. Use when the user says "how should I validate this", "cheapest way to test demand", "run a smoke test on my concept", or invokes /validation-patterns before committing engineering resources.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    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
  1. Distinctive:

    Ask the user: what are you trying to validate?

    line 30
  2. Very specific:

    If the validation produces a structured output (survey results, A/B data), write to artifacts/output/02-research/validation-results.md

    line 64

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Validation Patterns — Method Selection & Execution

What this skill does

Searches the 30-method validation catalog (methods.csv) and applies the best-fit validation pattern to test a product hypothesis before building. Covers smoke tests, concierge MVPs, customer discovery interviews, A/B test design, and more.

Persona delegation

This skill delegates to @founder. The founder selects and executes the validation method. The skill file provides the method catalog and selection logic; @founder provides the GO/RESHAPE/NO-GO judgment, challenge stance, and decision logging.

When to use

  • "How should I validate this idea?"
  • "What's the cheapest way to test demand?"
  • "Run a smoke test on my concept"
  • Pre-build validation before committing engineering resources

Workflow

Step 1: Understand the hypothesis

Ask the user: what are you trying to validate? What's the hypothesis? What would count as validation vs. invalidation?

Step 2: Select method

Run:

node .agents/scripts/match_methods.js --source validation --context "{user's hypothesis}"

Return the top 3-5 matching methods with relevance scores. Recommend the best one with reasoning. Let the user choose or accept the recommendation.

Step 3: Design the validation

Load the selected method from methods.csv. Design the validation:

  • Define the test (what will you do?)
  • Define the signal (what result validates the hypothesis?)
  • Define the duration and sample size
  • Identify confounds and edge cases

Step 4: Execute and record

Guide the user through execution. Record results:

@memory-controller write active-decisions.md
### [VALIDATION] {method name} — {hypothesis} [date: YYYY-MM-DD] [agent: @founder]
{method used, test design, results, verdict}
**Status:** active

Output artifacts

  • Validation design and results written to artifacts/memory/active-decisions.md
  • If the validation produces a structured output (survey results, A/B data), write to artifacts/output/02-research/validation-results.md

Done when — checked mechanically

This skill ships a catalog and a match_methods.js, and no gate of any kind — no Decision Gate step, no gate script, and nothing checks the verdict @founder is said to provide. The record format below is the entire artifact contract, and it is written from five lines of prose with no template.

node .agents/scripts/validation_record_check.js check \
  --file artifacts/output/02-research/validation-results.md --json

The gate applies to a structured validation record, and that file is optional. Step 4 writes the result to active-decisions.md; validation-results.md is produced only when the validation yields structured output (survey results, A/B data). This section used to invoke the gate against that path unconditionally, so a memory-only run — which followed every step — was told a required deliverable was missing. If there is no structured output, there is no record to check and the gate does not apply; say so in the memory entry rather than creating an empty file to satisfy a checker.

RuleWhat is checked
Record hygieneno unfilled template placeholders; a date in the declared [date: YYYY-MM-DD] form
Hypothesisstated, and substantive — the record format is [VALIDATION] {method} — {hypothesis}, and a validation with no hypothesis has no signal either
Method existsexactly one of the 30 in methods.csv. Exact, not substring: "Concierge MVP Extreme" is not a method
The signal, BOTH directionswhat validates and what invalidates. See below
A measurea duration or sample size containing a number — a signal without a denominator is not measurable
A confoundat least one named confound, alternative explanation or edge case
Verdictpresent, and from the declared GO / RESHAPE / NO-GO set

The signal is the centrepiece

Step 3 says "define the signal (what result validates the hypothesis?)" and nothing ever checked it — so the cheapest passing record defined success and stopped. Measured against a record that did exactly that:

"This validates the hypothesis if the click rate exceeds 15%. Demand exists… and we proceed to build the concierge flow."

→ 3 failures: no invalidation condition, no measure, no confound. A test that cannot fail is not a test, and a verdict reached by one is not a judgement — it is a preference. This is the same defect family as research-plan's {goal} — falsifiable? Yes/No, and it is the reason this gate exists.

What this gate does not check

Whether the test is a good test, whether the signal is the right signal, whether the confounds were the right confounds, or whether the verdict is correct. Those need a researcher. It stops a validation that was never designed from reading as one that was.

Record template

@memory-controller write active-decisions.md
### [VALIDATION] {method} — {hypothesis} [date: YYYY-MM-DD] [agent: @founder]

**Hypothesis:** {the claim, in enough detail that a result could contradict it}

**Method used:** {one of the 30 method_name values in methods.csv}.
Test: {what you will actually do, with whom, over how long}

**Signal.** This validates the hypothesis if {measurable result}. It invalidates the hypothesis if
{the result that would make you stop} — in which case we are wrong about {what} and should not build.

**Confounds.** {what else could explain the same result; selection bias; seasonal; promo; sample
already engaged}

**Verdict:** `[GO|RESHAPE|NO-GO]` — {the plain reason}

**Status:** active

Exit 0 conformant · 1 failures · 2 usage/IO error, fail-closed.

State machine integration

At start: run node .agents/scripts/orchestrator_state.js status At end: run node .agents/scripts/orchestrator_state.js complete --agent founder --artifact validation-results

Handoff

  • Hypothesis validated → load /shape-up or /design
  • Hypothesis invalidated → load /validate-idea (re-scope)
  • Need more research → load /explore-idea

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.