baoyu-danger-gemini-web
Generates images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation", or needs vision-capable AI generation.
66
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly articulates specific capabilities (text generation, image generation, vision input, multi-turn conversations), identifies the unique technology (reverse-engineered Gemini Web API), and provides explicit trigger guidance with natural user phrasings. The description is concise yet comprehensive, making it easy for Claude to select this skill appropriately.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Also specifies the mechanism (reverse-engineered Gemini Web API). | 3 / 3 |
Completeness | Clearly answers both 'what' (generates images and text via Gemini API with specific capabilities listed) and 'when' (explicit 'Use when' clause with trigger scenarios including backend usage and user request patterns). | 3 / 3 |
Trigger Term Quality | Includes natural trigger terms users would say: 'generate image with Gemini', 'Gemini text generation', 'image generation', 'vision-capable AI generation'. These cover likely user phrasings well. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific 'Gemini Web API' niche and the combination of image generation + vision input. The Gemini-specific triggers clearly distinguish it from other image generation or text generation skills. | 3 / 3 |
Total | 12 / 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 is a functional skill with strong actionability — the CLI examples are concrete, complete, and cover all major use cases well. The main weaknesses are moderate verbosity (the User Input Tools preamble, some redundant sections) and missing error handling/validation workflows for what is inherently a fragile reverse-engineered API integration. The progressive disclosure is adequate but could better leverage external files for reference material.
Suggestions
Add error handling guidance for common failures: authentication timeout, cookie expiration, API rate limits, and browser not found — with specific recovery steps for each.
Remove or significantly trim the 'User Input Tools' section, which describes generic agent behavior Claude already understands, and the redundant 'Extension Support' section that just points to Preferences.
Move the detailed options, models, and environment variables tables to a separate REFERENCE.md file, keeping only the most common options inline with usage examples.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient with good use of tables and code examples, but includes some unnecessary sections like the 'User Input Tools' preamble and the 'Extension Support' section that just points back to Preferences. The consent check flow is somewhat verbose for what it conveys. The authentication section has some unnecessary detail about CDP session reuse internals. | 2 / 3 |
Actionability | Provides fully executable CLI commands with concrete examples covering all major use cases (text generation, image generation, vision input, multi-turn conversations, JSON output). Options table is complete with flags and descriptions. Authentication and environment variable configuration are specific and actionable. | 3 / 3 |
Workflow Clarity | The consent check flow is well-sequenced with clear steps. However, there's no error handling guidance for common failure scenarios (authentication failures, API errors, cookie expiration). The script directory resolution steps are clear but lack validation checkpoints. For a reverse-engineered API skill involving browser automation, missing error recovery guidance is a notable gap. | 2 / 3 |
Progressive Disclosure | References EXTEND.md for configuration and mentions scripts/gemini-webapi/* for implementation details, which is good structure. However, without bundle files to verify, the references to EXTEND.md content are vague ('supports: Default model, proxy settings, custom data directory' without specifics). The skill is somewhat long with inline content that could be split (e.g., the full options/models/env vars tables could be in a reference doc). | 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
- jimliu/baoyu-skills
- Commit
bd5745f
- Reviewed
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