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AB horizon-trader

v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling, fractional differentiation, HRP, denoising), multi-strategy orchestration, alpha research, tier-gated features, and market discovery.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 4 773 tokens Open the sourcegithub.com↗ analyzed 2 d ago

v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage…

As a process B 66/100 · Nearly there — weak spots: inputs and preconditions

ProcedureData and analyticstype 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
93/100
safety, quality, tests
Safety 60%
95
Quality 40%
89
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
50
Tools and files w 18
60
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token SKILL.md:138
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python3 {baseDir}/scripts/horizon.py start-feed eth_usd chainlink '{"contract_address":"0x5f…419","rpc_url":"https://eth.llamarpc.com"}'
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:314
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      contract_address="0x5f…419",
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:323
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - ETH/USD: `0x5f…419`
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:324
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - BTC/USD: `0xF4…88c`
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:325
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - LINK/USD: `0x2c…27c`
      quoted

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "emoji"

    Process rating: all ten parameters 66/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Execution cost. Instruction body is 4773 tokens
    • 100Steps. 57 steps
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 13 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 329: enough signal without eating the budget
    • +4Structure: 44 headings
    • +3Step-by-step instructions: 57 items
    • +3Output format is stated explicitly
    • +4Has examples (23 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.