Conciseness

The body is dense with genuinely non-obvious specifics (flag-only CLI rules, per-widget versions, JSON gotchas), but the --dataset-catalog/--dataset-schema rule is repeated ~5 times (Quick Reference table, Step 2 note, Step 5 deploy comments, update comments, Implementation Guidelines §1) and the bare-table-name rule 3-4 times. It also explains design knowledge Claude already has ("~4-5% of viewers have color blindness", the 60/30/10 rule, "Don't put red and green adjacent"), so it could be tightened considerably.

Actionability

Fully executable throughout: copy-paste CLI blocks (including DASHBOARD_ID capture via jq and the mkdirs precondition), exact JSON skeletons, correct-vs-wrong field-matching examples, per-widget size tables, and a 13-item pre-deploy checklist. The commands cover all common cases (create, update, publish, trash, schema discovery, parallel multi-query probing).

Workflow Clarity

The NEW DASHBOARD CREATION WORKFLOW is a clearly sequenced 5-step process with explicit validation ("You MUST test ALL SQL queries via CLI BEFORE deploying", "gate on each object's state != \"SUCCEEDED\""), feedback loops ("Fix the query or adjust the story before moving on"), a pre-deploy quality checklist, and lifecycle rules for update→publish. Not 4: explicit checkpoints and error-recovery guidance (exit-code gotcha, 2>&1/jq pitfall) are present at every risky step.

Progressive Disclosure

Navigation is excellent: the Widget Index maps every widget type to a verified anchor in a reference file, the "What are you building?" and Reference Files tables route tasks to files, all 6 bundle reference files are linked, and references are one level deep. Not 5: the ~575-line body inlines reference-grade material (8 starter palettes of hex codes, detailed theme mechanics) that belongs in a reference file, and cross-skill links like ../databricks-metric-views/SKILL.md do not resolve within this bundle.

Specificity

"Create Databricks AI/BI dashboards" names the domain with essentially one capability statement; the actions "creating, updating, or deploying" appear only inside the trigger clause, and "CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly." are behavioral directives rather than capabilities. Not 4: the gaps are more than minor (no mention of widgets, filters, layout, or theming); not 2: the domain and dashboard lifecycle actions are explicitly named.

Completeness

It explicitly answers both questions: what ("Create Databricks AI/BI dashboards") and when ("Must use when creating, updating, or deploying Lakeview dashboards"), with concrete trigger phrases. Not 4: the 'when' clause is already explicit and specific, which is exactly what the 4-anchor flags as missing.

Trigger Term Quality

Natural user terms are present — "Databricks", "AI/BI dashboards", "Lakeview dashboards", "deploying" — including the key product-name synonym (Lakeview). Not 5: common phrasings a user might say such as "KPI", "chart", "visualization", or "dashboard JSON" are missing; not 3: the primary synonym variation is covered.

Distinctiveness Conflict Risk

"Databricks AI/BI" plus "Lakeview dashboards" pins a clear niche with distinct, product-specific triggers and minimal overlap risk; a user asking for this would not be routed to a generic document- or charting skill. Not 4: there is no meaningful overlap with a closely related skill's trigger terms.