Conciseness

Dense, operational guidance with no explanations of concepts Claude already knows; every section (node selection, the leading-'=' sharp edge, dataset boundary) earns its place, matching the lean-and-efficient anchor.

Actionability

Names concrete tool actions and every config/metric field, gives copy-paste expressions with correct/wrong examples, and defers full call recipes to the reference; per the scoring notes, absence of code in this instruction-only skill is not penalized because the guidance is actionable.

Workflow Clarity

A numbered six-step Default Procedure with explicit guards (approval-card checkpoint, 'Never invent a dataTableId', the leading-'=' rule) and a closing 'Close with facts' verification step; not 2 because checkpoints are explicit rather than implicit.

Progressive Disclosure

A concise overview body with one well-signaled, one-level-deep reference ('Use references/config-eval-playbook.md for tool-call recipes, worked examples, and output shapes') that is a real file holding appropriately deeper detail.

Specificity

Lists many concrete actions — 'set up, add, view, change, or remove… score, grade, or judge… measure answer quality' — matching the multiple-specific-actions anchor; not 2 because coverage is comprehensive rather than partial.

Completeness

Explicitly answers both what ('Builds and maintains configuration-based evaluations… with the eval-config tool') and when (an explicit 'Use when…' clause); the Use-when clause is present so completeness is not capped at 2.

Trigger Term Quality

'Use when the user asks to set up, add, view, change, or remove an evaluation, score, grade, or judge a workflow's output' uses natural verbs a user would actually say; good coverage, matching the anchor-3 example.

Distinctiveness Conflict Risk

Carves a clear niche — 'the only eval form Instance AI handles — it does not touch on-canvas evaluation nodes' — and explicitly excludes the competing form, making conflict unlikely.