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AC qstrader

AI Trading Assistant for quantumstocks.ru. Automated hedge fund with market analysis, risk management, and trade execution via n8n MCP. Use when analyzing markets, managing positions, risk checks, news, portfolio monitoring, trade journaling. Requires n8n MCP server with broker access.

ClawHub Agent Skills author: antonBy77 v1.0.0 MIT-0 10 files · 1 script body ≈ 1 432 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerZapierInfrastructureAI and agentstype 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
A
96/100
safety, quality, tests
Safety 60%
98
Quality 40%
93
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration read-dotenv README.md:44
      Reads a .env file
      cp ~/.openclaw/workspace/skills/qstrader/.env.example ~/.openclaw/workspace/skills/qstrader/.env
    • low Exfiltration read-dotenv SKILL.md:155
      Reads a .env file
      cp .env.example .env  # Заполнить свои ключи

    Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 53/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 26 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1432 tokens
    • 100Running it twice. No mutating operations

    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
    • +3Description length 286: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 4 scripts are documented
    • +2Bilingual instructions (RU + EN)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: suspicious
    This is a real broker-connected trading skill, and while its trading purpose is disclosed, it needs Review because it combines live account and order authority with weak scoping and unsafe setup/logging patterns.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026