Content
40%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 skill delivers concrete, runnable code but is overstuffed with repeated prompt templates that should be factored into reference files, and it lacks any sequencing or validation guidance for its sentiment workflows. Token efficiency and structure are the dominant weaknesses.
Suggestions
Collapse the nine near-identical function templates into a single parameterized pattern plus a short table of output schemas, moving the full per-domain JSON schemas into a references/ file linked from a compact overview.
Add a short workflow section ordering the typical flow (pick coin -> run sentiment -> cross-check whale/FUD signals -> sanity-check for bot/coordinated activity) with an explicit 'verify before acting on signals' checkpoint.
Show JSON parsing and basic error handling in at least the Quick Start example so outputs are actionable objects rather than raw strings.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is heavily padded: nine near-identical prompt templates with verbose, repeated JSON schemas that Claude could readily derive, plus redundant influencer lists and restated boilerplate, all of which inflates the token budget without adding proportional value. | 2 / 5 |
Actionability | Provides concrete, executable Python calling the xAI OpenAI-compatible endpoint with a real model id and copy-paste-ready function definitions; minor gaps are that no JSON-parsing or error-handling is shown and outputs are returned as raw strings. | 4 / 5 |
Workflow Clarity | Functions are presented as an unsequenced catalog with no ordering guidance, and the batch/destructive-adjacent operations (pump-and-dump flagging, manipulation signals) have no validation or verify-before-acting checkpoints, so the sequence and safety feedback loops are largely absent. | 2 / 5 |
Progressive Disclosure | A monolithic single-file dump: the large per-function JSON schemas and influencer list clearly belong in separate reference files, yet no bundle files exist and the only external links are general xAI docs rather than skill-specific references, so structure is minimal and references are buried. | 2 / 5 |
Total | 10 / 20 Passed |