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BD moltrade

Operate the Moltrade trading bot (config, backtest, test-mode runs, Nostr signal broadcast, exchange adapters, strategy integration) in OpenClaw.

ClawHub Agent Skills author: zhouhuihui008 v1.0.0 MIT-0 9 files body ≈ 2 618 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
97
Quality 40%
72
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token SKILL.md:188
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "router_address": "0xE5…564",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:190
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "default_token_in": "0xC0…Cc2",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:191
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "default_token_out": "0xA0…B48"
    quoted

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 40Consistency. Frontmatter name (moltrade) differs from the folder (moltrade-1-0-9)
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash, git, python) that frontmatter does not declare
  • 100Steps. 36 steps
  • 100Execution cost. Instruction body is 2618 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 tags): a typed call is more reliable

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 145: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (11 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This looks like a legitimate documentation-only trading skill, but it warrants Review because it guides agents toward live trading, sensitive key use, and public Binance Square posting with incomplete scoping.
LLM: suspicious (high) · VirusTotal: · 29 May 2026