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get-prompt-from-image

Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.

Quality

92%

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Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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.

A well-organized, directive skill body that offloads detail to three clearly signaled reference files and gives precise output constraints. The workflow is clearly sequenced but could add an explicit self-check/validation step on the generated prompts before final output.

Suggestions

Add an explicit validation checkpoint in the workflow (e.g., re-read the generated prompt against the 3-5 reproduction-critical anchors and confirm none were lost) before emitting the final output.

Tighten the Positive Prompt and Negative Prompt enumerated checklists into more compact guidance to reduce token load without losing the concrete constraints.

Consider condensing the Medium Boundaries bullet list into a shorter rule set, since several bullets restate the same 'exclude other media' idea for different mediums.

DimensionReasoningScore

Conciseness

Lean and directive with no padding about basic concepts Claude already knows; each section earns its place, though a few enumerated lists (e.g., the full Positive-Prompt checklist and Negative-Prompt categories) could be tightened slightly.

4 / 5

Actionability

Highly actionable instruction-only guidance with concrete constraints: 450-700 Chinese characters, ordered Chinese:/English: sections, 10-15 comma-separated negative phrases, and explicit placement rules (first third = visual anchors).

5 / 5

Workflow Clarity

A clear 9-step sequence from inspection to final output with explicit conditional branching (illustration-style applied only when relevant), but it lacks an explicit validation/feedback checkpoint on the produced prompts before output.

4 / 5

Progressive Disclosure

Well-structured overview pointing via clear markdown links to three real one-level-deep reference files (analysis-framework.md, category-guides.md, illustration-style.md), with conditional loading guidance so unrelated references are skipped.

5 / 5

Total

18

/

20

Passed

Description

95%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.

A strong, third-person description that cleanly states capability, gives rich natural trigger terms across many subject types, and sharpens distinctiveness with an explicit 'do not use' boundary. Minor room to broaden the concrete action verbs beyond analyze/reverse-engineer.

DimensionReasoningScore

Specificity

Lists several concrete actions ('Analyze user-provided reference images,' 'reverse-engineer high-fidelity AI image-generation prompts') with comprehensive subject-type coverage, but the action verbs are limited to analyze/reverse-engineer/extract rather than a broad multi-action list.

4 / 5

Completeness

Explicitly answers both what ('Analyze... and reverse-engineer high-fidelity AI image-generation prompts') and when ('Use when the user asks to recreate, imitate...'), reinforced by an explicit negative-trigger boundary ('Do not use for requests that only require OCR...').

5 / 5

Trigger Term Quality

Comprehensive natural trigger coverage including synonyms ('recreate, imitate, reverse-engineer, or extract prompts') plus a wide range of concrete subject types users would name (photographs, illustrations, 3D renders, logos, posters).

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (reverse-engineering image-gen prompts from reference images) with distinct triggers and an explicit anti-trigger that minimizes overlap with generic image-description or OCR skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

wuyoscar/GPT-Image2-Skill

Path

skills/get-prompt-from-image/SKILL.md

Reviewed

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