Conciseness

The body is lean and efficient — a one-line purpose statement, an env-var requirement, runnable commands, example flag invocations, and a three-item output listing, with zero padding or explanation of concepts Claude already knows. Every token earns its place, matching anchor 5; there is nothing extraneous to trim toward anchor 4.

Actionability

Commands are concrete and executable, and the flags shown (--count, --model, --size, --quality, --out-dir, --prompt) all match the actual script interface. It falls short of anchor 5 because paths are hardcoded to the author's environment ("python3 ~/Projects/agent-scripts/skills/openai-image-gen/scripts/gen.py") rather than being skill-relative or copy-paste ready elsewhere, and useful script capabilities like --dry-run and error/timeout behavior are omitted.

Workflow Clarity

The sequence (run script, open the generated gallery) is clear and the script path is concrete, but this is a batch operation — it fires N paid API calls — and the body includes no validation or verification checkpoint (e.g., running --dry-run first to preview prompts, or confirming outputs before opening the gallery). Per the judging guidelines, a batch skill without validation is capped at 3 even if single-purpose; it scores above anchor 2 because steps are concrete and unambiguous rather than vague.

Progressive Disclosure

This is a short single-purpose skill (~36 lines) whose only bundle file is scripts/gen.py, which exists and is what the Run section invokes; no external references are needed. The Setup / Run / Output sections are well-organized and appropriately sized for the SKILL.md overview role, matching the simple-skill exception for a top score.

Specificity

The description "OpenAI Images API: batches, prompt sampler, gallery" names the domain but lists feature nouns ("batches, prompt sampler, gallery") rather than concrete actions — there is no verb phrase at all, matching anchor 2 ('names the domain but actions are minimal or generic'). It is below anchor 3, which requires 1-2 concrete actions (e.g., 'generates images'), and above anchor 1 because the domain is named specifically.

Completeness

A partial 'what' can be deciphered (image generation in batches producing a gallery), but the 'when' is completely absent — there is no "Use when..." clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines. It is not 4 because 'when' guidance is missing entirely, not merely imprecise; not 2 because the 'what', while terse, is decipherable and domain-specific.

Trigger Term Quality

"OpenAI Images API" is a relevant keyword, but the natural phrases users would actually say — "generate images", "image generation", "create an image", "DALL-E" — are entirely absent; "batches", "prompt sampler", and "gallery" are weak trigger terms. This matches anchor 2 ('one or two relevant keywords; missing the natural phrases users say') rather than anchor 3, which requires broader synonym coverage.

Distinctiveness Conflict Risk

Naming the specific API ("OpenAI Images API") carves out a clear niche, so conflict risk with unrelated skills is low — matching anchor 4 ('mostly distinct; minor overlap risk with closely related skills'). It is below anchor 5 because the weak trigger phrasing leaves selection ambiguous against closely related image-generation skills.