blockrun
Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")
75
71%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agent/skills/blockrun/SKILL.mdQuality
Discovery
54%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 description excels at trigger terms and distinctiveness, providing excellent keywords users would naturally say when needing external model capabilities. However, it critically fails at explaining what the skill actually does - it only describes when to use it, not what actions it performs or what outcomes users can expect.
Suggestions
Add a 'what' clause at the beginning describing concrete actions, e.g., 'Integrates with external AI models to generate images, fetch real-time social media data, and access capabilities beyond Claude's native features.'
Specify the concrete outputs or results users can expect, such as 'Returns generated images, live tweets, or responses from specialized models.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names specific capabilities (image generation, real-time X/Twitter data) and mentions specific models (grok, gpt, dall-e, deepseek), but doesn't describe concrete actions the skill performs - only when to use it. | 2 / 3 |
Completeness | The description only answers 'when' (use when user needs capabilities Claude lacks or requests external models) but completely omits 'what' - it never explains what the skill actually does or how it works. | 1 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'blockrun', 'use grok', 'use gpt', 'dall-e', 'deepseek', 'image generation', 'real-time X/Twitter data'. These are specific phrases users would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Very distinct niche - external model integration and capabilities Claude lacks. The specific model names (grok, gpt, dall-e, deepseek) and 'blockrun' term create clear, unique triggers unlikely to conflict with other skills. | 3 / 3 |
Total | 9 / 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-structured skill that efficiently communicates BlockRun's capabilities with actionable code examples and clear trigger tables. The progressive disclosure to sub-skills is excellent. The main weakness is workflow clarity - while individual operations are clear, the overall flow (especially error handling and the relationship between setup and usage) could be more explicit.
Suggestions
Add a numbered quick-start workflow showing the complete flow: 1) Initialize wallet, 2) Fund if needed, 3) Make calls, 4) Check spending
Include error handling guidance for common failures (insufficient balance, API errors, network issues)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, using tables for quick reference and avoiding explanations of concepts Claude already knows. Every section serves a clear purpose without padding. | 3 / 3 |
Actionability | Provides fully executable Python code examples that are copy-paste ready, with clear import statements and method calls. The trigger tables give concrete guidance on when to use each capability. | 3 / 3 |
Workflow Clarity | The budget control section shows a validation pattern, but the overall workflow for using BlockRun lacks explicit sequencing. Missing clear step-by-step flow for first-time setup vs. subsequent usage, and no error handling guidance. | 2 / 3 |
Progressive Disclosure | Excellent structure with a concise overview in the main file and clear one-level-deep references to sub-skills for detailed topics (basic chat, image generation, search parameters, etc.). Navigation is well-signaled. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Repository
- Dokhacgiakhoa/antigravity-ide
- Commit
332e58b
- Reviewed
Table of Contents
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