Grade the evidence behind a claim before betting on it — the hierarchy for business evidence (experiments > usage data > surveys > interviews > anecdotes > opinion), the fit-for-decision test, and the mixed-evidence verdicts that real questions produce. Use when asked how strong is our evidence for this, grade what we know before the decision, is this enough to bet on, or we have three anecdotes and a survey — now what. Produces the evidence inventory with grades, the sufficiency verdict against the decision's stakes, and the cheapest-upgrade path.
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Use evidence-grading to inventory and grade the evidence for [claim and decision], using [itemized supporting and contradicting evidence] with [provenance, sample sizes, dates, and collection context], then provide a stakes-relative sufficiency verdict and cheapest upgrade path.
Required inputs
[claim and decision]
[itemized supporting and contradicting evidence]
[provenance, sample sizes, dates, and collection context]
User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗
SKILL.md
name: evidence-gradingdescription: "Grade the evidence behind a claim before betting on it — the hierarchy for business evidence (experiments > usage data > surveys > interviews > anecdotes > opinion), the fit-for-decision test, and the mixed-evidence verdicts that real questions produce. Use when asked how strong is our evidence for this, grade what we know before the decision, is this enough to bet on, or we have three anecdotes and a survey — now what. Produces the evidence inventory with grades, the sufficiency verdict against the decision's stakes, and the cheapest-upgrade path."
Evidence Grading Skill
"We have evidence" covers everything from a randomized experiment to the CEO's seatmate on a flight — and decisions made on ungraded evidence inherit the confusion. The grading discipline: inventory what actually supports the claim, place each item on the business-evidence hierarchy (what it is, not how confident it feels), test the graded weight against the decision's stakes (a reversible pilot needs less than a one-way rebrand — decision-journal logic), and when evidence falls short, name the cheapest upgrade — because the answer to weak evidence is usually a better test, not a braver bet.
What This Skill Produces
The evidence inventory — everything supporting (and contradicting) the claim, each item graded on the hierarchy
The weight assessment — what the graded pile actually supports, including the mixed-signals honest read
The sufficiency verdict — enough for this decision's stakes / not yet — with the stakes analysis shown
The upgrade path — the cheapest next evidence that would move the verdict ("a 2-week holdout test settles this for $0")
Required Inputs
Ask for these if not provided:
The claim and the decision riding on it — "users want X" feeding a backlog item vs. feeding a repositioning are different sufficiency bars; the decision's reversibility and cost set the bar
The evidence, itemized — every piece: the data pull, the survey, the five customer quotes, the competitor's move, the expert's opinion — including the inconvenient items (an inventory that omits contradicting evidence is advocacy)
The evidence's provenance — n, selection, dates, who collected it and with what incentive (source-triangulation supplies the externals; internal evidence has incentives too)
Framework: The Grading Rules
The hierarchy, applied without sentiment: experiments/A-B tests (causal) > usage/behavioral data (what people do, correlational) > surveys (what they say, at scale — survey-design-basics quality adjusts the grade) > interviews (rich, small-n — interview-synthesis counts matter) > anecdotes (existence proofs only) > expert opinion (informed priors) > internal conviction (a hypothesis, not evidence). Each item gets its rung and its quality-within-rung — a leading survey grades below honest interviews.
Direction and independence both count: the inventory includes contradicting evidence at its own grade, and echo-checks the supporting pile (three anecdotes traceable to one loud customer are one anecdote). The weight is the net, honestly netted.
Anecdotes prove existence, never prevalence: "a customer asked for X" establishes that the need exists somewhere — it cannot establish how common; the classic grading error is prevalence conclusions from existence evidence, and it's the error this skill most often catches.
Sufficiency is relative to stakes: the verdict tests weight against the decision — reversible-and-cheap decisions legitimately run on interview-grade evidence (the pilot is the experiment); irreversible-and-expensive ones demand behavioral or experimental grade. "Weak evidence" isn't a verdict; "weak for this bet" is.
The upgrade path is the constructive ending: when insufficient, name the cheapest test that would change the verdict — the holdout, the fake-door, the survey that sizes the interview theme, the pilot-with-metrics. Ranked by cost-to-confidence ratio; the skill's product is often not "no" but "this $0 two-week test first."