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")

Quality

71%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agent/skills/blockrun/SKILL.md

Quality

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 by naming specific external models and use cases, making it easy to identify when to select this skill. However, it critically fails at explaining what the skill actually does—it only describes when to use it, not the actions or capabilities it provides. The description is essentially a 'Use when...' clause without the preceding capability statement.

Suggestions

Add a capability statement before the 'Use when' clause explaining what the skill does (e.g., 'Delegates requests to external AI models and services to access capabilities beyond Claude's native abilities.')

Describe concrete actions the skill performs (e.g., 'Generates images via DALL-E, fetches real-time Twitter/X data via Grok, routes queries to GPT or DeepSeek models')

Restructure to follow the pattern: '[What it does]. Use when [triggers]' rather than starting with 'Use when'

Dimension	Reasoning	Score
Specificity	Names specific capabilities (image generation, real-time X/Twitter data) and mentions external models by name (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 X or says Y) but completely omits 'what' the skill actually does. There's no explanation of the skill's capabilities or actions.	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 delegation with specific model names and capability gaps. Unlikely to conflict with other skills due to explicit model names and unique use case of accessing external services.	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-crafted skill that efficiently communicates BlockRun's capabilities through tables and executable code examples. The progressive disclosure to sub-skills is excellent. The main weakness is workflow clarity - while individual operations are clear, the overall flow from initialization through various use cases could benefit from more explicit sequencing and error handling.

Suggestions

Add a numbered quick-start workflow showing the complete flow: 1) Initialize client, 2) Check balance, 3) Make first call, 4) Verify success

Include error handling guidance for common failures (insufficient balance, network issues, rate limits)

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%

Warnings & errors only

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: 3395991

Reviewed: 24 days ago

Table of Contents

Discovery Implementation Validation

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