AC polymarket-prediction-trades
Real-time streaming Polymarket prediction trades on Polygon (matic) with live USD pricing. Subscribe to a live stream of Polymarket prediction market trades over WebSocket: outcome trades (buyer, seller, amount, collateral in USD, price, order ID), market metadata (question title, resolution source, outcome labels), and transaction details — streamed in real time from the Bitquery GraphQL API. Covers all Polymarket markets including sports odds, Bitcoin Up or Down (and other crypto up/down markets), and general prediction markets.
As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, consistency
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "requires"
Process rating: all ten parameters 62/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (polymarket-prediction-trades) differs from the folder (polymarket-real-time-trades)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 29 steps
- 100Inputs and preconditions. Inputs and preconditions are listed
- 100Failures and branches. 4 branches, has a failure section
- 100Execution cost. Instruction body is 3099 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 10 top-level sections: this looks like several domains in one skill
- medium 4 test cases, all positive: not one "should refuse" or "should ask first"
- low No test case covers injection arriving through data
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 536: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.