Content
63%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is highly actionable — every use case ships executable code with a runnable Quick Start, concrete parameters, and costs — but it is a monolithic, repetitive file. Factorizing the repeated API-call boilerplate and splitting use-case examples into reference files would cut tokens substantially without losing clarity.
Suggestions
Show the client setup and one canonical `chat.completions.create` call once, then present the remaining use cases as just the prompt templates to eliminate ~10 repetitions of the same boilerplate.
Move the use-case examples (financial news monitoring, earnings reaction, competitor analysis) and the parameter/rate-limit tables into a `references/` file (e.g., USE_CASES.md), keeping SKILL.md to Quick Start, the Agent Tools pattern, and best practices.
Fix the type annotations in `monitor_financial_news` and `safe_x_search` (declared `-> dict`, return strings) and define or pass `client` in each standalone snippet so examples are self-contained.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body avoids explaining concepts Claude already knows, but the same `client.chat.completions.create(model="grok-4-1-fast", messages=[...])` boilerplate is repeated nearly verbatim in about ten snippets (Quick Start, topic search, ticker search, account monitoring, trending, agent tools, financial news, earnings, competitor, error handling), which could be factored into one canonical call plus prompt templates — noticeably tighter than anchor 4's 'minor instances'. | 3 / 5 |
Actionability | The Quick Start is copy-paste runnable and the use-case functions are concrete and executable with a parameters table and costs, matching 'mostly executable with minor gaps': a few snippets rely on an implicit global `client`, and `monitor_financial_news() -> dict` and `safe_x_search() -> dict` are annotated as returning dicts while returning strings. | 4 / 5 |
Workflow Clarity | The core action (call Grok with a search prompt) is unambiguous from the Quick Start, the Agent Tools API is clearly signaled as the advanced alternative, and an error-handling section provides a basic failure pattern; however, there is no explicit validation of responses (e.g., empty or stale results), so it fits anchor 4 rather than the explicit-checkpoint anchor 5. | 4 / 5 |
Progressive Disclosure | Sections are well organized with headers and tables, but this is a ~305-line monolithic SKILL.md with no bundle files: the eight-plus use-case code examples and the parameter/rate-limit tables are inline content that clearly belongs in one-level-deep reference files, matching anchor 3 ('content that should be separate is inline'). | 3 / 5 |
Total | 14 / 20 Passed |