AC fuku-predictions
Trade Kalshi prediction markets through conversation, powered by Fuku sports model predictions. Use when a user asks about Kalshi markets, wants sports predictions with edge analysis, wants to place or exit trades, or wants autonomous scanning. Supports CBB, NBA, NHL, and Soccer with personalized trading profiles. User defines preferences in natural language ("I want home dogs getting 7+ points in CBB"), agent builds a profile, scans markets, and presents opportunities with edge, payout, and recommendation. Kalshi API key stored locally — never transmitted externally.
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
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 · 2
✓ No critical or high findings
Medium and low: 2
-
medium Secrets in code
secret-private-keySKILL.md:34Private key material (key header without key body; quoted — discussed, not commanded)KALSHI_PRIVATE_KEY="-----BEGIN PRIVATE KEY----- …
header onlyquoted -
low Dangerous commands
cmd-cron-mentionscripts/setup.py:575Mentions editing / listing crontab (string literal in code, not executed)print(f"\nAdd this line to your crontab (crontab -e):")
code literal
Files scanned: 23. 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 53/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 14 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1759 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 574: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 10 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.