Measure whether the article embedding search works

Translate the claim into assertions or a tiny eval harness. The metric to protect is: top-1 article id match on gold queries; similarity in (-1,1). Always record the denominator (how many cases) beside any rate. A percentage without a denominator is marketing, not measurement.

const parsed = OutputSchema.safeParse(raw);
if (!parsed.success) {
  throw new ContractError("invalid_output", parsed.error.issues.map(i => ({
    path: i.path.join("."), code: i.code
  })));
}
return parsed.data;

Expected evidence: The query “reset password” returns the password-reset article first with a finite score.. A passing assertion proves only the behavior it names; broader usefulness still needs the chapter’s full limits.

Be explicit: beating the baseline (keyword overlap ranking on the same articles) on this fixture does not prove behavior under comparing raw tokens without vectors, or dimension mismatch. Label observations separately from conclusions so the next page inherits honest evidence about the article embedding search.

Compute top-1 article id match on gold queries; similarity in [-1,1] with the denominator written beside the rate every time. For this chapter, the evaluation set is intentionally tiny; that is allowed only if you say so in the evidence. Compare against keyword overlap ranking on the same articles before celebrating.

Add one negative case aimed at comparing raw tokens without vectors, or dimension mismatch. A suite with only happy cases cannot protect the article embedding search when the characteristic failure appears in review.

If a check is expensive or flaky, shrink it until it is deterministic on three short support articles + one gold query. Flaky green builds teach the team to ignore gates. Record what this page does not prove so security-ops and mastery-ship inherit honest limits.

At the evaluation stage for embedding-api-lab, the job is narrower than finishing a product demo. You are creating one progressive evidence piece about three short support articles + one gold query that later pages inherit without redefining success. Keep that fixture small enough to inspect by hand, keep outputs copy-pasteable as text, and refuse to narrate this baseline as if it were a production SLA: keyword overlap ranking on the same articles.

For this page specifically, success looks like metrics with explicit denominators and a negative case while still centering the user decision to rank articles by cosine similarity to an embedded query. If you cannot point to a file, command, or assertion that proves that for the article embedding search, stay on this page instead of advancing.

Glossary: tool · Glossary: structured output · Cheatsheet: production ops signals

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