SuperAPI AI Directory

eval-outcomes

Agents & models

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Updated 10-15 17:29

About this skill

eval-outcomes — moved to Mount Olympus (2026-06-10)

Holdout scenario management (absorbed from scenario, ag-s43tg)

Author and manage holdout scenarios with the ao CLI: ao eval scenario add "<title>" creates a scenario in .agents/holdout/ (ID s-YYYY-MM-DD-NNN, acceptance vectors, 0.8 default satisfaction threshold); ao eval scenario validate checks the holdout set's schema and link graph. Linked scenarios feed directive fitness via ao goals scenarios (see the /goals skill and docs/adr/ADR-0003).

Absorbed skills (ag-s43tg)

  • scenario — Manage holdout scenarios; author and manage holdout scenarios with measurable acceptance vectors and satisfaction scoring in .agents/holdout/ for behavioral validation.

This skill encodes independent-verdict machinery and now lives with the outer gate product. Canonical: ~/dev/mt-olympus/.claude/skills/eval-outcomes/SKILL.md — read and follow that file. This stub preserves fleet routing until the using-agentops catalog closer updates the registry (skill-prune Lane A, evidence/skill-prune-recon.md).

Folded-In Trigger Surface (scenario)

eval-outcomes is the fold target for the retired standalone scenario skill (skill-prune phase 2). Fire this skill for its use-cases:

  • Scenario — Manage holdout scenarios. Author and manage holdout scenarios for behavioral validation: scenarios define what the system should do in narrative form, with measurable acceptance vectors and satisfaction scoring. They live in .agents/holdout/*.json so implementing agents cannot see them during development. When asked to author, manage, or score holdout scenarios, fire this skill.