---
title: Plugin Hub Discovery, Ranking, and Reuse Economy
date: 2026-02-10
status: proposal
author: Larry the Laptop Lobster
---

# Plugin Hub Discovery, Ranking, and Reuse Economy

## Pitch
Create a plugin hub where users and agents can discover, rank, and reuse plugins, enabling a growing ecosystem of verified capabilities with economic incentives for contributors.

## Why
A vibrant plugin ecosystem accelerates PlanExe adoption and quality. Without discovery and ranking, useful plugins remain hidden and the system becomes fragmented.

## Problem

- No standardized marketplace for plugins.
- Quality and safety are inconsistent.
- Contributors lack incentives to improve or maintain plugins.

## Proposed Solution
Build a plugin hub that:

1. Hosts plugins with metadata, versioning, and usage stats.
2. Ranks plugins by quality, safety, and outcome performance.
3. Enables reuse and composability across plans.
4. Supports economic incentives for contributors.

## Core Components

### Plugin Registry

- Unique plugin IDs and semantic versioning.
- Metadata: domains, tasks supported, inputs/outputs.
- Security tier and safety certifications.

### Ranking and Discovery

- Ranking based on reliability, performance, and adoption.
- Search by task, domain, or required outputs.
- Personalized recommendations by usage patterns.

### Reuse Economy

- Credit system for plugin authors.
- Usage-based compensation or reputation gains.
- Maintenance incentives for high-usage plugins.

## Ranking Model

Rank plugins using a weighted score:

- Reliability score (crash rate, schema conformance)
- Quality score (benchmark outcomes)
- Adoption score (active usage, retention)
- Safety tier (penalty for lower tiers)

**Example formula:**

```
RankScore =
  0.35*Reliability +
  0.30*Quality +
  0.20*Adoption +
  0.15*SafetyTier
```

## Output Schema

```json
{
  "plugin_id": "plug_210",
  "version": "1.3.0",
  "ranking_score": 0.91,
  "downloads": 2480,
  "safety_tier": "Tier 1"
}
```

## Governance and Moderation

- Require safety certification for Tier 1 listing.
- Provide a takedown path for malicious or broken plugins.
- Enforce semantic versioning and compatibility checks.

## Integration Points

- Tied to runtime plugin safety governance.
- Uses benchmarking harness for quality scoring.
- Interfaces with plugin adaptation lifecycle.

## Success Metrics

- Growth in active plugins.
- Increase in reused plugins per plan.
- Contributor retention and maintenance rates.

## Risks

- Ranking manipulation or gaming.
- Low-quality plugin proliferation.
- Misaligned incentives for short-term usage over long-term quality.

## Future Enhancements

- Revenue sharing models.
- Federated plugin registries.
- Automated dependency compatibility checks.

## Detailed Implementation Plan

### Phase A — Retrieval Stack

1. Build semantic capability index for plugins.
2. Add feature store for rank signals (fit, reliability, recency, reuse).
3. Implement top-k retrieval with configurable cutoffs.

### Phase B — Ranking Model

1. Compute blended ranking score with policy-tunable weights.
2. Add duplicate detection and merge recommendations.
3. Add exploration mode for discovering undervalued plugins.

### Phase C — Feedback and Economy

1. Capture runtime success feedback per plugin use.
2. Adjust ranking via online updates with decay.
3. Reward stable high-performing plugins via visibility boosts.

### Validation Checklist

- Top-1 retrieval success rate
- Duplicate plugin creation reduction
- Reuse rate growth over time

