SKILLEMALL.ai
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AB reddit-stonks

Scrape Reddit stock pages (r/wallstreetbets, r/stocks, etc.) and use Deepseek AI to analyze which stock has the highest 1-week return potential. Includes a web app (uvicorn app:app). Use when the user asks about stock picks, Reddit stock sentiment, meme stocks, investing ideas from Reddit, "what should I buy", "best stock this week". Supports --euro flag for European exchange equivalents.

ClawHub Agent Skills author: Altus v1.1.1 MIT-0 10 files body ≈ 401 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

AnalyzerInfrastructuretype 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
94/100
safety, quality, tests
Safety 60%
96
Quality 40%
90
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Exfiltration read-dotenv README.md:22
      Reads a .env file
      cp .env.example .env   # add DEEPSEEK_API_KEY
    • low Exfiltration read-dotenv README.md:32
      Reads a .env file
      cp .env.example .env
    • low Exfiltration read-dotenv SKILL.md:24
      Reads a .env file
      cp .env.example .env
    • low Exfiltration read-dotenv stonks.py:253
      Reads a .env file (quoted — discussed, not commanded)
      "Copy .env.example to .env and add your key."
      quoted

    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 65/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 401 tokens

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 391: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 13 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill does what it claims: it analyzes public Reddit and market data with DeepSeek, but users should understand the external AI and finance-advice risks.
    LLM: benign (high) · VirusTotal: · 29 May 2026