💎 SkillPrism

Progressive Skill Disclosure & Context Compaction Engine for Autonomous AI Coding Agents
Preloading hundreds of enterprise tool schemas dilutes model attention and inflates token costs. SkillPrism indexes skills out-of-context and injects only what the model needs, right when it needs it.

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⚡ The Problem: Context Bloat & Attention Dilution

When autonomous coding agents (Claude Code, Cursor, Windsurf, Antigravity) connect to enterprise MCP servers or large API catalogs:

• ~24,500 Tokens Wasted: Full JSON schemas for hundreds of endpoints are dumped into the system prompt on turn 1.
• Model Hallucinations: When models face 100+ tools, tool selection accuracy drops dramatically ("Lost in the Middle").
• Token Cost Explosion: Every reasoning turn repeatedly transmits schemas the agent never touches.

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💡 The Solution: SkillPrism Progressive JIT Disclosure

SkillPrism moves the entire tool catalog outside the LLM context:

1. Zero-State (~199 tokens): The agent prompt starts with only two meta-tools: search_skills and load_skill.
2. Sub-Millisecond BM25 Hybrid Search (< 0.1 ms): The agent queries for capabilities by natural intent (e.g. "query Postgres database").
3. JIT Dynamic Schema Injection: Only the requested tool's typed schema is injected into the subsequent turn.
4. Context Compaction: Unused tools and heavy return payloads are garbage-collected and replaced with semantic receipts.

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🚀 Quickstart

Installation

# Run CLI directly via npx
npx @ritualdev-lab/skillprism search "postgres database query"

# Or install locally
pnpm add @ritualdev-lab/skillprism

Programmatic Usage

import { SkillIndex } from "@ritualdev-lab/skillprism";

const index = new SkillIndex();

// Register tool schemas into out-of-context index
index.register({
  id: "postgres_query",
  name: "PostgreSQL Query Exec",
  summary: "Executes parameterized read queries against production PostgreSQL clusters",
  description: "Performs read-only SQL queries with built-in connection pooling and PII redaction.",
  category: "database",
  tags: ["sql", "postgres", "db", "query"],
  permissions: ["db:read"],
  parameters: [
    { name: "sql", type: "string", description: "The SQL statement", required: true },
    { name: "params", type: "array", description: "Query bind variables" }
  ]
});

// Import tools directly from standard MCP servers (tools/list)
index.importFromMcp(mcpToolsList);

// Search for matching skills with zero prompt bloat
const matches = index.search("fetch user records from postgres", 3);
console.log(matches[0].disclosureSnippet);

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🛠️ Client Integration Adapters

Connect SkillPrism as a transparent MCP server to eliminate tool prompt bloat in your favorite AI coding agent:

1. Claude Code CLI

Add SkillPrism to your Claude Code workspace:

claude mcp add skillprism -- npx -y @ritualdev-lab/skillprism proxy --stdio

Or configure directly in claude.json:

{
  "mcpServers": {
    "skillprism": {
      "command": "npx",
      "args": ["-y", "@ritualdev-lab/skillprism", "proxy", "--stdio"]
    }
  }
}

2. Cursor IDE (~/.cursor/mcp.json)

Add to your Cursor global or workspace MCP configuration:

{
  "mcpServers": {
    "skillprism": {
      "command": "npx",
      "args": ["-y", "@ritualdev-lab/skillprism", "proxy", "--stdio"]
    }
  }
}

3. Windsurf IDE (~/.codeium/windsurf/mcp_config.json)

{
  "mcpServers": {
    "skillprism": {
      "command": "npx",
      "args": ["-y", "@ritualdev-lab/skillprism", "proxy", "--stdio"]
    }
  }
}

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💻 CLI Commands

# Search out-of-context index by natural intent
npx @ritualdev-lab/skillprism search "upload file to s3"

# Ingest and convert OpenAPI 3.0/3.1 specs
npx @ritualdev-lab/skillprism import ./api-spec.json

# Fetch and index tools from a running MCP server
npx @ritualdev-lab/skillprism add http://localhost:3000/mcp

# Run verifiable BPE token benchmark
npx @ritualdev-lab/skillprism benchmark

# Sync verified community tools from DevShelf directory
npx @ritualdev-lab/skillprism sync

# Start transparent MCP stdio or HTTP proxy
npx @ritualdev-lab/skillprism proxy --stdio
npx @ritualdev-lab/skillprism proxy --port 8080

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📊 Live Benchmark Results

⚡ SkillPrism Token Optimization & Latency Benchmark

📦 Catalog Size: 100 Enterprise Tools
🔴 Unoptimized Preload Zero-State: ~11,989 tokens
🟢 SkillPrism JIT Zero-State:       ~326 tokens (3 meta-tools)
🚀 Upfront Token Savings:           97.3%
⏱️ Average Search Latency:          < 0.3 ms
💾 Payload Compaction Savings:      91.0%

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💖 Community & Commercial Support

• Website & Live Demo: skillprism.ritualdev.in
• Donations: Support independent open-source AI tooling research via donation.rolenest.in.
• Enterprise & Turnkey: Need custom private MCP servers or enterprise skill gateways? Visit mcp.ritualdev.in or contact contact@ritualdev.in.
• Developer Inquiries & Support: Reach out directly to developer@ritualdev.in or support@ritualdev.in.

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👥 Team & Contributors

SkillPrism is initiated and maintained by the team at RitualDev Lab and expanded by the open-source AI community.

🛡️ Core Team & Maintainers

Divyanshu Jethi 🚀 Founder & Lead

Sakshi Sharma 🎨 Core Maintainer & Product

RitualDev ⚙️ Core Maintainer & Infra

Divyanshu-hub-dotcom 🛠️ Core Member

Ayush 🛡️ Core Maintainer & Triage

🌟 Community Contributors & Builders

Huge thanks to all our open-source Contributors! We warmly welcome issues, feedback, and pull requests.

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📄 License

Apache-2.0 © 2026 RitualDev Lab.