---
title: Near-Match Plugin Adaptation Lifecycle
date: 2026-02-10
status: proposal
author: Larry the Laptop Lobster
---

# Near-Match Plugin Adaptation Lifecycle

## Pitch
Enable safe, low-friction adaptation of existing plugins when they almost fit a new task, reducing duplication and increasing reuse while maintaining quality controls.

## Why
Most new plugin requests are variants of existing capabilities. Without a formal adaptation lifecycle, teams either fork plugins ad hoc or rebuild from scratch, creating fragmentation and quality drift.

## Problem

- Duplicate plugins proliferate without a clear adaptation path.
- Unreviewed modifications introduce bugs and regressions.
- No consistent record of what changed, why, and with what impact.

## Proposed Solution
Create a formal adaptation lifecycle with stages:

1. Detection of near-match plugins.
2. Structured gap analysis.
3. Controlled modification and testing.
4. Validation and promotion to production.

## Lifecycle Stages

### Stage 1: Near-Match Detection

- Use semantic similarity on plugin metadata and required outputs.
- Identify the closest plugin candidates.
- Produce a ranked short list with compatibility scores.

### Stage 2: Gap Analysis

- Compare expected inputs/outputs with target requirements.
- Identify missing capabilities and output mismatches.
- Classify gaps as minor (parameter changes) or major (logic change).

### Stage 3: Adaptation

- Apply targeted modifications:
  - Input schema extensions
  - Output formatting changes
  - Parameter tuning
  - New edge-case handling

### Stage 4: Testing

- Run benchmark tests against known scenarios.
- Compare performance with original plugin.
- Validate output schema compatibility.

### Stage 5: Promotion

- Approve adapted plugin into registry.
- Assign new semantic version.
- Attach adaptation notes and rationale.

## Output Schema

```json
{
  "plugin_id": "plug_301",
  "adapted_from": "plug_212",
  "gap_summary": ["Add JSON schema X", "Handle multi-currency"],
  "test_status": "pass",
  "version": "2.1.0"
}
```

## Integration Points

- Linked to plugin hub discovery and benchmarking harness.
- Uses safety governance for runtime loading.
- Feeds change logs into audit trails.

## Success Metrics

- Reduction in duplicate plugins.
- Faster delivery of adapted plugins.
- Lower regression rates after adaptation.

## Risks

- Over-reliance on near-match detection can hide better designs.
- Incomplete testing leads to silent failures.
- Version sprawl without governance.

## Future Enhancements

- Automated adaptation suggestions.
- Cross-plugin dependency mapping.
- Adaptation impact scoring.

## Detailed Implementation Plan

### Phase A — Near-Match Retrieval

1. Retrieve top-k plugins by capability similarity.
2. Compute fit score against target contract.
3. Select adaptation candidate above threshold.

### Phase B — Adaptation Pipeline

1. Branch plugin version for adaptation.
2. Apply scoped modifications with test inheritance.
3. Validate backward compatibility and performance.

### Phase C — Promotion and Rollback

1. Canary adapted versions in limited traffic.
2. Auto-promote on success criteria.
3. Auto-rollback on regression signals.

### Validation Checklist

- Adaptation success vs full re-synthesis
- Regression incidence after promotion
- Rollback mean time to recovery

