Conciseness

The body is efficient and dense: concrete commands, RAM-to-model tables, and an error table with no explanations of concepts Claude already knows. Minor trimmable items remain — the dangling unlinked "Hardware sizing guide: RAM requirements by model parameter count and quantization level" line and duplication of the model table and install commands between the body and skill-workflow.md. Not 3 because there is no unnecessary explanation, and not 5 because of that duplication and the loose Resources line.

Actionability

Mostly executable guidance: "brew install ollama && brew services start ollama", "curl -fsSL https://ollama.com/install.sh | sh", a complete docker run command, "ollama pull llama3.2", and verification via "curl http://localhost:11434/api/tags". Not 5 because steps 7-10 lack specifics ("Set up GPU acceleration if NVIDIA or Apple Silicon hardware is detected" and "Validate end-to-end inference latency and throughput" name no commands), and integration code lives only in the referenced file; not 3 because the core workflow is copy-paste executable.

Workflow Clarity

A clear 10-step ordered sequence with explicit validation checkpoints (step 5 test prompt "ollama run llama3.2 'Say hello'", step 6 REST API curl check, step 10 performance validation) plus an error-handling table for recovery. Not 5 because steps 7-10 (integration, GPU setup, persistence, performance validation) lack checkpoints and verification commands, leaving minor validation gaps.

Progressive Disclosure

Good structure with clearly signaled one-level-deep references ([references/skill-workflow.md](references/skill-workflow.md) and [references/errors.md](references/errors.md), both real files) and appropriately concise inline content. Not 5 because references/examples.md (523 lines of expanded examples) is never linked from the body, and skill-workflow.md largely duplicates the body's model and installation content rather than adding a distinct layer.

Specificity

Names the domain and one concrete action ("Configure ... Ollama" for local LLM deployment, free AI alternatives, eliminating hosted API costs), but the broken "Configure auto-configure" phrasing and lack of any further actions (install, model selection, verification) limit it to 1-2 concrete actions. It is above anchor 2 because a concrete action with a clear purpose is present, and below anchor 4 because no additional specific actions are listed.

Completeness

Both what ("Configure ... Ollama" for local deployment) and when (explicit trigger phrase list) are present, matching anchor 4. Not 5 because the actual "Use when" clause is template filler ("Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.") rather than concrete trigger guidance; not 3 because the when is explicit via the trigger phrase list, not merely implied.

Trigger Term Quality

Good natural keyword coverage: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs" are phrases users would plausibly say. Not 5 because common variants like "offline AI", "run models locally", or "local inference" are missing; not 3 because coverage goes well beyond a few generic keywords.

Distinctiveness Conflict Risk

Ollama-specific triggers ("install ollama") establish a clear niche with minimal conflict risk, but broad phrases like "replace OpenAI" and "no API costs" could also match other local-LLM or API-migration skills. This is the "mostly distinct; minor overlap risk" anchor rather than 5's minimal conflict risk.