🌑 Liquid Shadow

The AI-Native Intelligence OS

Liquid Shadow is the primary bridge between your reasoning engine and the raw filesystem. It doesn't just "index" code; it builds a Relational Intelligence Graph that allows AI agents to navigate, reason about, and modify large-scale repositories with surgical precision and extreme token efficiency.

Stop forcing your agents to grep through files. Give them the ability to "feel" the architecture through topological maps and execution flows.

Product Pillars

Semantic Sieve & Token Efficiency

Context is the most expensive resource. Our Semantic Sieve intelligently folds implementation details, revealing only the signatures and intent your agent needs. With Briefing Zoom Levels (Orbit, Atmosphere, Ground), you control exactly how many tokens are consumed based on the task's altitude.

Nano-Repair & Structural Stability

Repositories are liquid. Code moves, files are renamed, and dependencies shift. Nano-Repair auto-heals your intelligence index in real-time, ensuring that "intent links" and architectural context survive even the most aggressive refactors.

Mission-Driven Development

We treat development as a series of tactical Missions. Liquid Shadow records every architectural decision (ADR), discovery, and blocker as it happens, creating a persistent "Chronome" of project narrative that persists across sessions.

Relational Impact Analysis

Change one function, see the ripple. Trace execution flows and predict the Blast Radius of any modification across repository boundaries using our cross-repo fusion engine.

The Tactical Suite (31 Atomic Tools)

Organized into specialized intelligence suites for the modern agent:

| Suite | Tactical Purpose | Key Tools | | :--------------- | :------------------------------ | :------------------------------------------------- | | Ops Control | Mission & context management | shadow_ops_context, shadow_ops_briefing | | Intelligence | Deep architectural reasoning | shadow_analyze_impact, shadow_analyze_flow | | Discovery | Semantic & config retrieval | shadow_search_concept, shadow_search_config | | Recon | Structural layer classification | shadow_recon_topography, shadow_recon_hologram | | Inspection | Token-optimized code folding | shadow_inspect_symbol, shadow_inspect_file | | Maintenance | Intelligence synchronization | shadow_sync_trace, shadow_sync_repair |

The Intelligence Lifecycle

Liquid Shadow is designed to be the first point of contact for any agent entering a workspace.

1. Installation (Safe Init)

npm install -g @precisionutilityguild/liquid-shadow
liquid-shadow init # Interactive security confirmation

2. Operational Dashboard (TUI)

Keep a finger on the pulse of your repository's intelligence. Liquid Shadow provides a high-signal Terminal UI for a bird's-eye view of your mapping density and performance.

liquid-shadow dashboard

Scouting Report: Need a quick status instead? Run liquid-shadow status.

3. The Skills-First Loop

Liquid Shadow is designed for Autonomy. While it provides 31 atomic tools, the primary interface for an agent is the Skills system. Running liquid-shadow init automatically injects these high-level workflows into the agent's environment.

High-Signal Workflows

Instead of guessing which tools to call, agents follow optimized Tactical Skills:

• /onboard: Build the baseline index and topography.
• /understand: Concept-to-code mapping and execution tracing.
• /mission: Strategic planning and automated ADR synthesis.
• /trace-impact: Predict blast radius and dependency ripple effects.
• /audit: Detect technical debt, circular deps, and dead code.

Example: Agent Strategy Flow

// 1. RECON: The agent reads the Skill definition
view_file({ path: '.agent/skills/onboard/SKILL.md' });

// 2. ACT: Following the Skill, the agent orchestrates the tools
shadow_recon_onboard({ repoPath: '/abs/path' });
shadow_ops_context({ repoPath: '/abs/path' });
shadow_env_hooks({ action: 'install', repoPath: '/abs/path' });

Enterprise-Grade Performance

Optimized for speed. Scalable for large codebases.

• VS Code Core (6.1k files): Indexed in 110.6s (109k+ symbols)
• Next.js (9.7k files): Indexed in 24.2s (~404 files/sec)