nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
Advanced context management with auto-compaction and dynamic context optimization for DeepSeek's 64k context window. Features intelligent compaction (merging, summarizing, extracting), query-aware relevance scoring, and hierarchical memory system with context archive. Logs optimization events to chat.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install ad2546/context-optimizerInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Advanced context management optimized for DeepSeek's 64k context window. Provides intelligent pruning, compression, and token optimization to prevent context overflow while preserving important information.
import { createContextPruner } from './lib/index.js';
const pruner = createContextPruner({
contextLimit: 64000, // DeepSeek's limit
autoCompact: true, // Enable automatic compaction
dynamicContext: true, // Enable dynamic relevance-based context
strategies: ['semantic', 'temporal', 'extractive', 'adaptive'],
queryAwareCompaction: true, // Compact based on current query relevance
});
await pruner.initialize();
// Process messages with auto-compaction and dynamic context
const processed = await pruner.processMessages(messages, currentQuery);
// Get context health status
const status = pruner.getStatus();
console.log(`Context health: ${status.health}, Relevance scores: ${status.relevanceScores}`);
// Manual compaction when needed
const compacted = await pruner.autoCompact(messages, currentQuery);
// When something isn't in current context, search archive
const archiveResult = await pruner.retrieveFromArchive('query about previous conversation', {
maxContextTokens: 1000,
minRelevance: 0.4,
});
if (archiveResult.found) {
// Add relevant snippets to current context
const archiveContext = archiveResult.snippets.join('\n\n');
// Use archiveContext in your prompt
console.log(`Found ${archiveResult.sources.length} relevan...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
Advanced context management optimized for DeepSeek's 64k context window. Provides intelligent pruning, compression, and token optimization to prevent context overflow while preserving important information.
# Install dependencies
npm install
# Or install globally for CLI use
npm install -g .
import { createContextPruner } from './lib/index.js';
const pruner = createContextPruner({
contextLimit: 64000, // DeepSeek's limit
autoPrune: true,
strategies: ['semantic', 'temporal', 'extractive'],
});
await pruner.initialize();
// Process messages with automatic pruning
const messages = [
{ role: 'user', content: 'Hello!', priority: 5 },
{ role: 'assistant', content: 'Hi there!', priority: 5 },
// ... more messages
];
const processed = await pruner.processMessages(messages);
// Get status
const status = pruner.getStatus();
console.log(`Health: ${status.health}`);
console.log(`Tokens: ${status.tokens.used}/${status.tokens.limit}`);
# Run tests
node scripts/cli.js test
# Show status
node scripts/cli.js status
# Prune a JSON file
node scripts/cli.js prune input.json output.json
# Show statistics
node scripts/cli.js stats
Removes semantically similar messages using embeddings. Useful for eliminating redundant information.
Removes older messages first, preserving recent conversation. Configurable preservation of recent messages.
# Context Pruner
Advanced context management optimized for DeepSeek's 64k context window. Provides intelligent pruning, compression, and token optimization to prevent context overflow while preserving important information.
## Key Features
- **DeepSeek-optimized**: Specifically tuned for 64k context window
- **Adaptive pruning**: Multiple strategies based on context usage
- **Semantic deduplication**: Removes redundant information
- **Priority-aware**: Preserves high-value messages
- **Token-efficient**: Minimizes token overhead
- **Real-time monitoring**: Continuous context health tracking
## Quick Start
### Auto-compaction with dynamic context:
```javascript
import { createContextPruner } from './lib/index.js';
const pruner = createContextPruner({
contextLimit: 64000, // DeepSeek's limit
autoCompact: true, // Enable automatic compaction
dynamicContext: true, // Enable dynamic relevance-based context
strategies: ['semantic', 'temporal', 'extractive', 'adaptive'],
queryAwareCompaction: true, // Compact based on current query relevance
});
await pruner.initialize();
// Process messages with auto-compaction and dynamic context
const processed = await pruner.processMessages(messages, currentQuery);
// Get context health status
const status = pruner.getStatus();
console.log(`Context health: ${status.health}, Relevance scores: ${status.relevanceScores}`);
// Manual compaction when needed
const compacted = await pruner.autoCompact(messages, currentQuery);
```
### Archive Retrieval (Hierarchical Memory):
```javascript
// When something isn't in current context, search archive
const archiveResult = await pruner.retrieveFromArchive('query about previous conversation', {
maxContextTokens: 1000,
minRelevance: 0.4,
});
if (archiveResult.found) {
// Add relevant snippets to current context
const archiveContext = archiveResult.snippets.join('\n\n');
// Use archiveContext in your prompt
console.log(`Found ${archiveResult.sources.length} relevan...# Context Pruner
Advanced context management optimized for DeepSeek's 64k context window. Provides intelligent pruning, compression, and token optimization to prevent context overflow while preserving important information.
## Features
- **DeepSeek-optimized**: Specifically tuned for 64k context window
- **Multiple pruning strategies**: Semantic, temporal, and extractive compression
- **Adaptive pruning**: Different strategies based on context usage levels
- **Priority-aware**: Preserves high-priority and system messages
- **Real-time monitoring**: Continuous context health tracking
- **Token-efficient**: Minimizes token overhead from pruning operations
## Installation
```bash
# Install dependencies
npm install
# Or install globally for CLI use
npm install -g .
```
## Quick Start
```javascript
import { createContextPruner } from './lib/index.js';
const pruner = createContextPruner({
contextLimit: 64000, // DeepSeek's limit
autoPrune: true,
strategies: ['semantic', 'temporal', 'extractive'],
});
await pruner.initialize();
// Process messages with automatic pruning
const messages = [
{ role: 'user', content: 'Hello!', priority: 5 },
{ role: 'assistant', content: 'Hi there!', priority: 5 },
// ... more messages
];
const processed = await pruner.processMessages(messages);
// Get status
const status = pruner.getStatus();
console.log(`Health: ${status.health}`);
console.log(`Tokens: ${status.tokens.used}/${status.tokens.limit}`);
```
## CLI Usage
```bash
# Run tests
node scripts/cli.js test
# Show status
node scripts/cli.js status
# Prune a JSON file
node scripts/cli.js prune input.json output.json
# Show statistics
node scripts/cli.js stats
```
## Pruning Strategies
### 1. Semantic Pruning
Removes semantically similar messages using embeddings. Useful for eliminating redundant information.
### 2. Temporal Pruning
Removes older messages first, preserving recent conversation. Configurable preservation of recent messages.
### 3. Extractive...AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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