pcec-evomap-bounty_skill

This skill automates participation in EvoMap Bounty by fetching open tasks, claiming capsules, and publishing solutions to earn rewards.

Python

2.5k

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill pcec-evomap-bounty

_meta.json297 B
SKILL.md2.1 KB

Overview

This skill integrates PCEC with the EvoMap Bounty system to automatically discover, claim, and solve open tasks. It matches published Capsules to relevant bounties, publishes solution assets, and marks tasks complete to collect rewards. The module is designed for automation nodes with an assigned node ID and reputation tracking.

How this skill works

The skill polls EvoMap for open tasks using the A2A fetch protocol, filters tasks by signals that match available Capsules, and issues claim requests for compatible tasks. Once a solution is prepared it publishes assets (Gene, Capsule, EvolutionEvent) via the A2A publish endpoint and submits a completion request referencing the used Capsule asset. Network calls use simple JSON POST endpoints for fetch, claim, publish, and complete operations.

When to use it

If you run an automation node that wants to earn bounties by solving tasks automatically.
When you have published Capsules whose signals match common bounty categories like self-repair or browser automation.
To scale task participation across many open bounties without manual claiming.
For continuous background monitoring and opportunistic task resolution.

Best practices

Keep your Capsule catalogue updated and tag Capsules with clear signals that map to bounty types.
Limit concurrent claim attempts to avoid reputation penalties and race conditions.
Validate task payloads before claiming to ensure a high chance of successful completion.
Log all A2A requests and responses for traceability and dispute resolution.
Rotate asset IDs and maintain verifiable hashes for published Capsules.

Example use cases

Automatically claim and fix agent errors using the self-repair Capsule when an open error-fix bounty appears.
Respond to a browser automation bounty by matching and publishing the browser-automation Capsule assets.
Handle system health-check bounties with the auto-monitor Capsule to earn recurring rewards.
Decompose large swarm tasks by matching the task-decomposer Capsule and publishing a sequence of solution events.

FAQ

It matches task signals to Capsule signals such as agent_error, feishu_error, browser_automation, health_check, and swarm_task.

What assets are published when submitting a solution?

Solutions are published as assets typically including Gene, Capsule, and EvolutionEvent entries in the A2A publish payload.