openai-image-gen
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
Install with Tessl CLI
npx tessl i github:qsimeon/openclaw-engaging --skill openai-image-gen72
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 92%
↑ 1.06xAgent success when using this skill
Validation for skill structure
Discovery
40%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 identifies a clear, distinctive capability but suffers from missing explicit trigger guidance and incomplete natural language keywords. The technical specificity is good for distinguishing from other skills, but the lack of a 'Use when...' clause significantly limits Claude's ability to know when to select this skill.
Suggestions
Add a 'Use when...' clause with trigger phrases like 'when the user wants to generate multiple AI images', 'batch image creation', or 'create an image gallery'
Include common user terms like 'DALL-E', 'AI images', 'generate pictures', 'bulk image generation' to improve trigger term coverage
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (OpenAI Images API) and mentions specific outputs (random prompt sampler, index.html gallery), but doesn't comprehensively list all actions like prompt configuration, batch size options, or image format handling. | 2 / 3 |
Completeness | Describes what it does (batch-generate images, create gallery) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | Includes some relevant terms like 'batch-generate images', 'OpenAI Images API', and 'gallery', but misses common user phrases like 'DALL-E', 'AI images', 'image generation', 'create pictures', or 'bulk images'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of 'OpenAI Images API', 'batch-generate', 'random prompt sampler', and 'index.html gallery' creates a very specific niche that is unlikely to conflict with other image or API skills. | 3 / 3 |
Total | 8 / 12 Passed |
Implementation
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-crafted skill that efficiently documents an image generation tool with excellent actionability through numerous executable examples. The model-specific parameter tables are particularly useful. The main weakness is the lack of error handling guidance or validation steps for what could be a flaky operation (API timeouts, rate limits, invalid API keys).
Suggestions
Add a brief troubleshooting section covering common failures: missing/invalid API key, timeout handling, rate limits
Include a validation step to verify the API key is set before running (e.g., check OPENAI_API_KEY environment variable)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Content is lean and efficient, providing only necessary information about flags, model parameters, and outputs without explaining what image generation is or how APIs work. | 3 / 3 |
Actionability | Provides fully executable bash commands with multiple real-world examples covering different models, sizes, and options. Commands are copy-paste ready with clear flag demonstrations. | 3 / 3 |
Workflow Clarity | The workflow is simple (run script, open gallery), but lacks validation checkpoints. No guidance on handling failures, checking API key setup, or verifying successful generation before opening gallery. | 2 / 3 |
Progressive Disclosure | Well-organized with clear sections (Run, Model-Specific Parameters, Output). Content is appropriately sized for a single file without needing external references. Easy to scan and find relevant information. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
72%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 8 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
metadata_field | 'metadata' should map string keys to string values | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 8 / 11 Passed | |
- Reviewed
Table of Contents
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