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BF vibetrading-code-gen

Generate executable Hyperliquid trading strategy code from natural language prompts. Use when a user wants to create automated trading strategies for Hyperliquid exchange based on their trading ideas, technical indicators, or VibeTrading signals. The skill generates complete Python code with proper error handling, logging, and configuration using actual Hyperliquid API wrappers.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 21 files body ≈ 5 514 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Generate executable Hyperliquid trading strategy code from natural language prompts.

As a process F 44/100 · Will not run — References files that are not bundled: templates/custom/, scripts/template_registry.py

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: templates/custom/, scripts/template_registry.py
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5514 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: templates/custom/
  • warning missing-ref reference to a missing file: scripts/template_registry.py

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: templates/custom/, scripts/template_registry.py
  • 0Tools and files. 2 referenced file(s) missing: templates/custom/, scripts/template_registry.py
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 8 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Steps. 227 steps, 5 vague phrases
  • 70Execution cost. Instruction body is 5514 tokens
  • 100Result and completion. Output format and completion criterion are stated
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 18 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -35 of 8 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 381: enough signal without eating the budget
  • +4Structure: 83 headings
  • +3Step-by-step instructions: 227 items
  • +3Output format is stated explicitly
  • +4Has examples (19 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.