SKILLEMALL.ai

BC orcatrace

Polymarket intelligence for AI agents — track smart money, see what others miss. Real-time prediction-market signals across 42K markets: quality-gated repricings with order-book microstructure, tracked-whale entries annotated with each wallet's hold-to-resolution calibration (follow/fade), and AI-detected predetermined-outcome markets — one unified feed. Plus the 4-hourly Intelligence Digest, markets resolving soon, whale calibration tables, and $1 single-market deep research. Pay-per-call via x402 (USDC on Base only); no accounts, no API keys. Free /v1/index, /v1/pulse, /v1/digest/brief, /v1/sample, and /v1/track-record (a verifiable whale scorecard) expose the funnel and every paid shape before you pay.

ClawHub Agent Skills author: Julius v1.0.0 MIT-0 2 files body ≈ 2 422 tokens Open the sourceclawhub.ai analyzed 2 d ago

Polymarket intelligence for AI agents — track smart money, see what others miss.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 51/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2422 tokens
  • 100Running it twice. Mutating operations check current state

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 714: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 6 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This is a disclosed API guide for Polymarket intelligence, with expected privacy and payment considerations but no hidden code or install behavior.
LLM: benign (high) · VirusTotal: · 10 Jul 2026