SKILLEMALL.ai
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AA alphaear-signal-tracker

Use this skill to track the evolution of an existing finance or investment signal when the user provides a prior thesis/signal and asks whether new market information strengthens, weakens, falsifies, realizes, or leaves it unchanged. It should compare baseline logic with updated news, prices, and fundamentals, then output a structured signal update. Use mx-search and mx-data for fresh facts as needed; do not use for simple news lookup, raw data lookup, stock screening, or diagram-only requests.

ClawHub Agent Skills author: LULI v1.0.0 MIT-0 38 files body ≈ 541 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

Use this skill to track the evolution of an existing finance or investment signal when the user provides a prior thesis/signal and asks whether new market…

As a process A 81/100 · Runs to the end — weak spots: running it twice, progress reporting

ProcedureData and analyticsAI 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
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
88
Run on models
none yet
Process rating
A
81/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
Failures and branches w 10
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 Secrets in code secret-high-entropy-token scripts/utils/hybrid_search.py:22
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      model_name: 向量模型名称，默认使用 para…-v2
      quoted
    • low Secrets in code secret-high-entropy-token scripts/utils/hybrid_search.py:34
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      self.model_name = model_name or os.getenv("EMBEDDING_MODEL", "para…-v2")
      quoted

    Files scanned: 36. 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 81/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 22 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 541 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4No input/output examples
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 499: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    The skill is not clearly malicious, but it ships broad finance research, forecasting, training, and database-writing capabilities beyond its narrow signal-tracker description.
    LLM: suspicious (high) · 27 Jul 2026