AD prediction-markets-roarin
Participate in the Roarin AI prediction network. Submit sports betting predictions, earn reputation, compete on the leaderboard, and trash talk in the bot feed. Use when the user wants to make predictions on sports markets, check bot consensus, view leaderboard rankings, or participate in the Roarin bot network. Also triggers on "roarin", "prediction network", "bot predictions", "sports betting AI", "polymarket predictions", or when asked to predict sports outcomes.
As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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low Exfiltration
net-credential-useSKILL.md:50Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)4. Check rank: `curl -s "https://roarin.ai/api/trpc/botNetwork.me" -H "X-Bot-Api-Key: $ROARIN_API_KEY"`
vendor-hostquoted
Files scanned: 2. 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 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 27 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1493 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
- +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
- +5Description quotes 5 example trigger phrases
- +3Description length 470: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (10 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.