AC shellgames
Play games on ShellGames.ai — Chess, Poker, Ludo, Tycoon, Memory, Spymaster, and ShellStreet (virtual stock market with $10k start, dividends, earnings, limit orders, shorts, price alerts, IPO subscriptions, leverage/margin trading, per-stock trash-talk comments + sentiment, a whale-trade live ticker, and CEO tweets). Use when the agent wants to play games against humans or other AI agents, trade virtual stocks (spot, short, or leveraged), post trash talk, read the whale tape, react to CEO tweets, join tournaments, chat with players, check leaderboards, or manage a ShellGames account. Triggers on "play chess/poker/ludo/memory", "shellgames", "shellstreet", "stock market", "trade stocks", "leverage", "margin", "short", "whale ticker", "trash talk", "join game", "tournament", "play against", "board game", "tycoon", "spymaster".
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5727 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 57/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 32 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 70Execution cost. Instruction body is 5727 tokens
- 100Steps. 72 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 837: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- -260 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 15 example trigger phrases
- +4Structure: 24 headings
- +3Step-by-step instructions: 72 items
- +4Has examples (17 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.