context-distiller

Senior Context Architect & Memory Engineer. Expert in Automated Context Packing, Symbol Indexing, and Agent Rehydration for 2026.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "context-distiller" with this command: npx skills add yuniorglez/gemini-elite-core/yuniorglez-gemini-elite-core-context-distiller

🗺️ Skill: Context Distiller (v1.1.0)

Executive Summary

The context-distiller is the master of high-fidelity information management for AI swarms. In 2026, the success of a mission depends on the quality and density of the context provided to the agent. This skill focuses on Automated Context Packing, building Symbolic Project Maps, and managing Agent Memory Rehydration to ensure that every session starts with maximum intelligence and minimum token noise.


📋 Table of Contents

  1. The Distillation Protocol
  2. The "Do Not" List (Anti-Patterns)
  3. Automated Context Packing (Repomix)
  4. Symbolic Project Mapping
  5. Agent Memory & Rehydration
  6. Hierarchical Inheritance
  7. Reference Library

🛠️ The Distillation Protocol

Before initiating a new mission or subproject, the Distiller MUST:

  1. Codebase Scan: Use rg and list_directory to map the active module's boundaries.
  2. Essence Extraction: Apply the Impeccable Distill logic—identify the 20% of code that provides 80% of the value. Strip away "Noise" (boilerplate, unused imports, redundant logic).
  3. Symbol Indexing: Generate a list of critical types and interfaces.
  4. Inheritance Audit: load master rules from docs/AGENTS.md.
  5. Local Rehydration: Create or read .gemini/GEMINI.md for mission-specific context.
  6. Context Packing: Bundle all findings into a structured Markdown artifact.

🚫 The "Do Not" List (Anti-Patterns)

Anti-PatternWhy it fails in 2026Modern Alternative
Thin ContextLeads to hallucinations and generic code.Use High-Fidelity Packing.
Token BloatHigh latency and poor reasoning.Use Semantic Filtering.
Flat HistoryAgent loses track of past decisions.Use Memory Rehydration.
Manual Symbol HuntSlow and prone to missing definitions.Use Symbolic Project Maps.
Ignoring RulesInconsistent architecture.Use Hierarchical Inheritance.

📦 Automated Context Packing

We use Repomix and gitingest to feed the models:

  • Structure: Group files by domain (Logic, Types, Tests).
  • Optimization: Exclude noise (node_modules, dist, git).
  • Security: Mandatory secret scrubbing before ingestion.

See References: Context Packing for workflows.


🐘 Symbolic Project Mapping

When projects are large, don't read everything—use a map.

  • JSON Maps: Indexing every export and its file path.
  • Symbolic RAG: fetching only relevant files based on symbol dependency.

📖 Reference Library

Detailed deep-dives into Information Engineering:


Updated: January 22, 2026 - 21:40

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Automation

subagent-orchestrator

No summary provided by upstream source.

Repository SourceNeeds Review
Automation

git-automation

No summary provided by upstream source.

Repository SourceNeeds Review
General

filament-pro

No summary provided by upstream source.

Repository SourceNeeds Review
General

pdf-pro

No summary provided by upstream source.

Repository SourceNeeds Review