Conciseness

The body is dominated by dense, high-signal tables, terse MUST rules, and code, but the PARTITIONED BY / CLUSTER BY rule is a ~120-word run-on sentence that would be clearer as a small table, and version-sensitive details ("DBR 18 LTS+", "Iceberg library 1.9.0+") sit in the main flow rather than a compatibility/deprecated section. This fits the efficient-with-minor-trimmable-instances anchor at 4; it never explains concepts Claude already knows, so it stays above 3.

Actionability

Quick Start provides copy-paste-ready SQL for all three table-creation patterns with exact TBLPROPERTIES, plus an executable ALTER TABLE for enabling UniForm, and Common Issues gives concrete commands and properties ("set `write.parquet.compression-codec` to `snappy`", "Check status with `DESCRIBE EXTENDED`"). Specific executable examples cover the common cases, matching the fully-executable anchor at 5.

Workflow Clarity

A "MUST determine which Iceberg pattern fits" rule plus the When-to-Use routing table establishes a clear decision sequence, and verification guidance exists (DESCRIBE EXTENDED status checks), but the UniForm enable workflow lacks an inline verify checkpoint — status checking appears only later in Common Issues. This fits the clear-sequence-with-minor-validation-gaps anchor at 4 rather than the explicit-checkpoint anchor at 5.

Progressive Disclosure

A ~150-line overview routes to five real, one-level-deep reference files (all verified to exist and contain substantive content, with only sibling cross-links, no nested chaining), each with a summary, keyword list, and When-to-Use routing entry. Content is appropriately split (1,130 lines of detail in references vs. a lean overview), matching the clear-overview/well-signaled-references anchor at 5.

Specificity

Lists multiple concrete actions across all sub-features — "creating Iceberg tables", "enabling External Iceberg Reads (uniform) on Delta tables", "configuring external engines to read Databricks tables via Unity Catalog IRC", "integrating with Snowflake catalog to read Foreign Iceberg tables" — with comprehensive coverage of managed tables, UniForm, compatibility mode, IRC, Iceberg v3, PyIceberg, OSS Spark, and credential vending. This matches the anchor for multiple specific concrete actions with comprehensive coverage; no meaningful gaps pull it to 4.

Completeness

The first sentence explicitly answers "what" by enumerating concrete capabilities, and "Use when creating..., enabling..., configuring..., integrating with Snowflake catalog..." explicitly answers "when" with concrete trigger phrases. This mirrors the anchor example that clearly and explicitly answers both what and when; nothing is left merely implied.

Trigger Term Quality

Natural user phrases are comprehensively covered with synonyms: "Iceberg tables", "External Iceberg Reads (fka Uniform)" (explicitly includes the legacy name), "Streaming Tables and Materialized Views", "Snowflake", "PyIceberg", "OSS Spark". These are the terms a user would naturally say when needing this skill; synonym coverage is essentially complete, so it exceeds the good-coverage anchor at 4.

Distinctiveness Conflict Risk

The description occupies a clear Iceberg-on-Databricks niche with distinct triggers (UniForm, IRC, compatibility mode), but "Snowflake interop" and the Delta-table triggers carry minor overlap risk with closely related Databricks-Delta, Unity Catalog, or Snowflake skills. It fits the mostly-distinct anchor at 4 rather than the minimal-conflict anchor at 5, while being far more specific than the overlap examples at 3.