openai-image-gen
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
63
57%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./openclaw/skills/openai-image-gen/SKILL.mdQuality
Discovery
50%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 concise and identifies a clear, distinctive niche (batch image generation via OpenAI API with gallery output). However, it completely lacks a 'Use when...' clause, which is critical for Claude to know when to select this skill. The trigger terms are somewhat technical and may not match how users naturally phrase requests.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user wants to generate multiple images in bulk, create an image gallery, or use the OpenAI/DALL-E API for batch image creation.'
Include more natural user-facing trigger terms such as 'DALL-E', 'generate images', 'image gallery', 'bulk image creation', or 'AI-generated images'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple concrete actions: batch-generate images, random prompt sampling, and generating an index.html gallery. These are specific, actionable capabilities. | 3 / 3 |
Completeness | Describes what it does (batch-generate images, prompt sampling, gallery creation) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, missing 'Use when' caps completeness at 2, and the 'when' is entirely absent, warranting a 1. | 1 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'images', 'OpenAI Images API', 'gallery', and 'batch-generate', but misses common user terms like 'DALL-E', 'image generation', 'create images', or 'bulk images'. Users may not naturally say 'batch-generate' or 'prompt sampler'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of OpenAI Images API, batch generation, random prompt sampling, and HTML gallery output creates a very distinct niche that is unlikely to conflict with other skills. | 3 / 3 |
Total | 9 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides strong actionability with concrete, executable commands and good coverage of model-specific options. However, the extensive parameter reference section makes the file longer than necessary for the main SKILL.md, and the lack of error handling or validation guidance for API calls (rate limits, failures, invalid parameter combinations) is a notable gap.
Suggestions
Move the detailed model-specific parameters section to a separate REFERENCE.md file and link to it from the main skill, keeping only the most essential defaults inline.
Add error handling guidance: what to do when API calls fail, rate limits are hit, or invalid parameter combinations are used.
Add a brief validation step, e.g., checking that OPENAI_API_KEY is set before running, and verifying output files were created successfully.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The model-specific parameters section is quite detailed and reference-like, which could be trimmed or moved to a separate file. However, most content is useful and not overly padded with things Claude already knows. | 2 / 3 |
Actionability | Provides fully executable commands with concrete flags and examples covering multiple models and configurations. The run commands are copy-paste ready with clear flag explanations. | 3 / 3 |
Workflow Clarity | The workflow is essentially a single command invocation, which is clear, but there's no validation or error handling guidance. The timeout warning is helpful, but there's no feedback loop for failures (e.g., API errors, rate limits, invalid parameters). | 2 / 3 |
Progressive Disclosure | The model-specific parameters section is extensive inline content that could be split into a reference file. The structure is reasonable with clear sections, but the detailed parameter tables bloat the main skill file. | 2 / 3 |
Total | 9 / 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 | |
- Repository
- trpc-group/trpc-agent-go
- Commit
af8bd5f
- Reviewed
Table of Contents
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