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Install in OpenClaw
/install polymarket-autopilot-experimental
Description
Skill sperimentale per l’analisi automatica di mercati pubblici Polymarket con simulazione paper trading, controllo dei costi LLM e report in italiano con mi...
Usage Guidance
This skill describes behavior that needs LLM API access (OpenAI and Anthropic) and precise token/cost accounting, but the published metadata lists no credentials — that's the main red flag. Before installing: 1) Ask the publisher which environment variables or provider integrations the skill expects and why they were omitted from the metadata. 2) If you supply API keys, create low-quota or billing-limited keys (or use separate sandbox accounts) so accidental cost is limited. 3) Confirm the platform/agent can enforce the stated frequency (1 run / 3 days) and the hard budget stop (2 € / week); if enforcement depends solely on the agent following instructions, it may fail. 4) Request clarification on the concrete method for token accounting and what happens when budget is exceeded. 5) Monitor activity and logs on first runs, and do not provide wallet/private keys. Absence of code and scanner findings reduces install risk, but the credential mismatch and vague stopping rules justify caution.
Capability Analysis
Type: OpenClaw Skill
Name: polymarket-autopilot-experimental
Version: 0.1.1
The skill explicitly states multiple strong constraints against malicious behavior, including 'no real transactions', 'no wallets', 'read-only access only', and 'works exclusively on public data'. It also details mechanisms for LLM cost control and self-limitation. There are no instructions for data exfiltration, unauthorized execution, persistence, or prompt injection attempts to bypass these constraints. All stated objectives and operational logic in SKILL.md align with a benign, experimental paper-trading simulation.
Capability Assessment
Purpose & Capability
The SKILL.md explicitly requires using OpenAI and Anthropic for analysis and for tracking token usage/costs. The registry metadata, however, declares no required environment variables, no primary credential, and no config paths. A skill that calls external LLMs would normally require API keys or declared credentials; the absence of these declarations is an incoherence.
Instruction Scope
Most runtime instructions stay within the stated purpose (read-only public Polymarket data, paper trading simulation, limited outputs). However the instructions require: (a) calling two LLM providers (OpenAI and Anthropic), (b) tracing token consumption and estimating euro costs, and (c) enforcing per-execution frequency and a weekly budget limit. Those items grant the agent broad discretion (e.g., "ridurre la complessità"), and the SKILL.md gives no precise enforcement mechanism — e.g., how token accounting is measured, which API keys are used, or what happens if the platform cannot reliably stop execution when budget is exceeded.
Install Mechanism
This is an instruction-only skill with no install spec and no code files — lowest installation risk. Nothing is downloaded or written to disk by an install step.
Credentials
The skill requires access to external LLM services and must track usage for cost control, but it declares no environment variables or credentials. That is disproportionate/unreported: at minimum you should expect API keys/tokens for OpenAI and Anthropic (or equivalent provider integrations). Also, implementing reliable budget enforcement may require access to billing/usage APIs or platform-level quotas — none of which are declared.
Persistence & Privilege
No 'always: true', no install, no write-to-disk steps described, and the skill does not request persistent privileges or modifications to other skills. Autonomous invocation is allowed by default (normal) but not elevated here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install polymarket-autopilot-experimental - After installation, invoke the skill by name or use
/polymarket-autopilot-experimental - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.1
Bugfix publish / retry Windows
v0.1.0
- Prima versione sperimentale della skill per l’analisi automatica di mercati pubblici Polymarket con simulazione di paper trading.
- Accesso solo in modalità read-only; nessun uso di wallet, transazioni reali o denaro reale.
- Analisi e simulazione con controllo rigoroso dei costi LLM (budget 2 € a settimana, massimo una esecuzione ogni 3 giorni).
- Output dettagliato in italiano: risultati simulati, costi, commento e mini-riassunto.
- Progettata per test autonomi a basso budget, anche da utenti non esperti di mercati.
- Arresto automatico se il budget viene superato o se il valore simulato non giustifica i costi.
Metadata
Frequently Asked Questions
What is Polymarket Autopilot Experimental?
Skill sperimentale per l’analisi automatica di mercati pubblici Polymarket con simulazione paper trading, controllo dei costi LLM e report in italiano con mi... It is an AI Agent Skill for Claude Code / OpenClaw, with 374 downloads so far.
How do I install Polymarket Autopilot Experimental?
Run "/install polymarket-autopilot-experimental" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Polymarket Autopilot Experimental free?
Yes, Polymarket Autopilot Experimental is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Polymarket Autopilot Experimental support?
Polymarket Autopilot Experimental is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Polymarket Autopilot Experimental?
It is built and maintained by mauonga (@mauonga); the current version is v0.1.1.
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