BC aionmarket-trading
Core trading skill for AION Market prediction market agents. Provides agent setup, wallet binding, market search, automated pre-trade checks, risk-aware trading, order management, position monitoring, and settlement workflows on Polymarket and Kalshi via the aion-sdk Python package. Use when: an AI agent needs to register, configure wallets, search markets, place or cancel trades, monitor positions, or run settlement-related flows on AION Market / Polymarket / Kalshi.
As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.
Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
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medium Risky intent
intent-wallet-secretsskill.md:44Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target| **Wallet Private Key** | `WALLET_PRIVATE_KEY` env var or `.env` | `0xabc123...` (64 hex chars, Polygon) |
-
low Secrets in code
secret-high-entropy-tokenskill.md:526High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| Polymarket (Polygon) | `0xeA…79B` |
table -
low Secrets in code
secret-high-entropy-tokenskill.md:527High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| Kalshi (Solana) | `CHMk…XcX` |
table
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7251 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 7251 tokens
- 85Steps. 91 steps, 2 vague phrases
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 19 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 473: enough signal without eating the budget
- +4Structure: 49 headings
- +3Step-by-step instructions: 91 items
- +4Has examples (22 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.