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image-poster

Single-image generation skill for posters, key art, and editorial illustrations. Defaults to gpt-image-2 but is provider-agnostic — the same workflow drives Flux, Imagen, or Midjourney via the active upstream tooling. Output is one or more PNG/JPEG files saved to the project folder.

61

Quality

77%

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tessl review fix ./design-templates/image-poster/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a tight, executable workflow: a structured prompt-composition checklist, a copy-paste-ready dispatcher command, and clear hard rules, with no padding. The main defects are the absence of a worked assembled-prompt example and a resource map that points to an example.html file that does not exist in the bundle.

Suggestions

Add a short worked example of a fully assembled prompt (e.g. filled-in values for model, aspect, and prompt string) so the happy path is demonstrated end-to-end.

Fix the resource map: either include example.html in the bundle or remove/adjust the entry so it does not advertise a file that does not exist.

Add a lightweight validation step after dispatch, e.g. check the returned JSON file name exists in the project folder before reporting the hand-off summary.

DimensionReasoningScore

Conciseness

The body is lean throughout: a two-sentence framing, a 5-point prompt-assembly checklist, one annotated dispatcher command, a hand-off rule, and four hard rules. Every section adds non-obvious information and nothing explains concepts Claude already knows, matching the "lean and efficient; every token earns its place" anchor rather than the "minor instances of over-explanation" of 4.

5 / 5

Actionability

The dispatcher command is copy-paste ready with clearly annotated placeholders (e.g. `--model "<imageModel from metadata>"`, `--prompt "<the full assembled prompt from Step 1>"`) and the composition checklist gives concrete, ordered guidance. It falls short of anchor 5 because the body never shows a worked example of a fully assembled prompt string, so the most common case is not demonstrated end-to-end.

4 / 5

Workflow Clarity

Steps 0-3 are clearly sequenced (read metadata, compose prompt, dispatch, hand off) with an explicit decision rule ("Ask only when the choice would materially change the requested result") and post-conditions (the command prints one line of JSON). Not a 5 because there is no validation checkpoint on the dispatcher output or the written file, and not a 3 because the sequence and most checkpoints are present.

4 / 5

Progressive Disclosure

The body is self-contained and well organized with clear sections, but the resource map advertises `example.html` ("← what the resulting card looks like in Examples") and no such bundle file exists in references/, scripts/, assets/, or the skill root. The sole referenced path is a dangling reference, which is more than the "minor organization gaps" of anchor 4.

3 / 5

Total

16

/

20

Passed

Description

66%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific and well-scoped, clearly stating what the skill does, its provider-agnostic model handling, and its output contract. Its main weakness is the absence of any "Use when..." trigger guidance, which caps completeness, and a few natural trigger synonyms are missing.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user asks for a poster, key art, cover art, or editorial illustration, or mentions generating an image/illustration asset."

Add common natural variations such as "artwork", "banner", "flyer", or "album cover" to broaden the natural-term coverage.

State when NOT to use it (e.g. multi-image sequences, photo editing of existing files) to further reduce overlap with adjacent image skills.

DimensionReasoningScore

Specificity

"Single-image generation skill for posters, key art, and editorial illustrations", "Defaults to gpt-image-2 but is provider-agnostic — the same workflow drives Flux, Imagen, or Midjourney", and "one or more PNG/JPEG files saved to the project folder" name the domain plus concrete specifics (models, formats, output destination). Not a 5 because it covers essentially one action (generate an image) rather than multiple distinct actions; not a 3 because the model/format/output details go beyond 1-2 generic actions.

4 / 5

Completeness

The "what" is clear (single-image generation for posters/key art/illustrations, provider-agnostic, PNG/JPEG output to the project folder), but the description contains no "Use when..." clause or equivalent explicit trigger guidance. Per the judging guidelines, a missing "when" caps completeness at 3.

3 / 5

Trigger Term Quality

Natural terms like "posters", "key art", "editorial illustrations", "image", and provider names (Flux, Imagen, Midjourney) give good keyword coverage. A few natural phrases users might say ("artwork", "banner", "flyer", "album cover") are missing, so it fits anchor 4 rather than the comprehensive synonym/extension coverage of 5.

4 / 5

Distinctiveness Conflict Risk

The poster/key-art/editorial-illustration niche is clearly distinguishable from document, data, or code skills. Minor overlap risk remains with a general image-generation skill via the generic "image" term, keeping it below the minimal-conflict anchor 5.

4 / 5

Total

15

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

nexu-io/open-design

Path

design-templates/image-poster/SKILL.md

Reviewed

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