SKILLEMALL.ai
GitHub ↗ RU Sign in

AB signalradar

Monitors Polymarket prediction markets for probability changes and sends alerts when thresholds are crossed. Supports AI model releases, crypto, and geopolitics categories. Use when user asks to "check prediction markets", "monitor Polymarket", "track market probabilities", "set up market alerts", or "watch AI/crypto/geopolitics predictions". Do NOT use for stock market analysis, sports betting, or real-time trading signals. 监控 Polymarket 预测市场概率变化，超过阈值时推送通知。支持 AI 模型发布、加密货币、 地缘政治三大类别。不适用于股市分析、体育博彩或实时交易信号。

modbender/skill-library-mcp Agent Skills author: modbender MIT 32 files · 1 script body ≈ 2 436 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Monitors Polymarket prediction markets for probability changes and sends alerts when thresholds are crossed.

As a process B 75/100 · Nearly there — weak spots: result and completion, inputs and preconditions

IntegrationNotionInfrastructureSoftware developmentAI 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
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
B
75/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
100
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 · 0

    ✓ No critical or high findings

    Files scanned: 32. 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 75/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 28 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2436 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low 10 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

    • +3Output format is not stated: the model decides each time
    • -316 of 18 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 509: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 28 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (5 of 9)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.