Conciseness

The body is dense with actionable specifics (exact tool names, apiVersion/kind values, REQUIRED/OPTIONAL parameter labels) and wastes no tokens explaining concepts Claude already knows. Not 5 because of redundancy: the MCP tool list appears in Prerequisites and again via the Dependencies section, the DNS/port-forward workaround is fully stated in Prerequisites and then repeated in Common Issues Issue 2, and "If rhoai unavailable or returns error" fallback boilerplate is restated per step. Not 3 because these are minor duplications rather than unnecessary explanation.

Actionability

Every step names the exact MCP tool, its parameters with REQUIRED/OPTIONAL flags, exact apiVersion `modelregistry.opendatahub.io/v1alpha1` and kinds, a copy-ready `oc port-forward svc/modelregistry-sample 8085:8085 -n rhoai-model-registries` command, and per-step error-handling branches. As an instruction-only skill the guidance is fully executable by an agent; per the rubric's scoring notes, absence of code is not penalized when guidance is this concrete.

Workflow Clarity

Seven steps are clearly sequenced with an explicit routing table ("Route: Browse/List -> Step 2, View -> Step 3, Register -> Step 4..."), validation checkpoints (namespace validation via `list_data_science_projects`, ModelRegistry instance check, PVC cross-namespace storage warning), HITL gates ("WAIT for user confirmation" in Steps 4-6), and error-recovery feedback loops per step. Not 4 because validation and error recovery are explicit rather than having minor gaps.

Progressive Disclosure

The body is a clear overview with well-signaled one-level-deep references ([skill-conventions.md], [openshift-fallback-templates.md], [common-issues.md#model-registry-internal-dns-unreachable]), and all referenced files exist in the bundle. Not 5 because two bundle reference files (known-model-profiles.md, live-doc-lookup.md) are never referenced or navigated from the body, and the DNS troubleshooting detail is inlined in Prerequisites even though it also lives in common-issues.md — content that should be split is duplicated inline. Not 3 because structure and signaling are otherwise good.

Specificity

The description lists multiple specific concrete actions: "Register, version, and manage ML models", "Browse the Model Catalog, track model metadata, and promote models across environments", plus "model registration, versioning, metadata management, artifact tracking, and cross-environment promotion" — comprehensive coverage of the skill's capabilities with no vague filler. Not 4 because coverage is comprehensive rather than having minor gaps.

Completeness

Clearly answers both questions: an explicit multi-sentence "what" (registration, versioning, metadata, artifacts, promotion) and an explicit "Use when:" block with five concrete trigger phrases, plus negative boundaries ("NOT for deploying models (use /model-deploy)"). Not 4 because neither what nor when could be more explicit.

Trigger Term Quality

The "Use when" list provides natural user phrasings like "Register a new model in the registry", "What versions exist for my model?", and "Promote a model from dev to production". Not 5 because a few natural variations are missing (e.g., browsing/finding models in the catalog is a capability but has no trigger phrase); not 3 because the quoted triggers are exactly what users would say, not generic keywords.

Distinctiveness Conflict Risk

Clear niche (OpenShift AI Model Registry lifecycle) with distinct triggers and explicit disambiguation against adjacent skills ("NOT for deploying models (use /model-deploy)", "NOT for model performance monitoring (use /ai-observability)"). Minimal conflict risk; not 4 because the negative boundaries remove even the minor overlap with related skills.