Skillget

immune

agent
Security Audit
Warn
Health Pass
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 10 GitHub stars
Code Warn
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-1.js
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-2.js
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-3.js
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-4.js
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-5.js
  • fs module — File system access in benchmark/comparison/superpowers-immune/round-6.js
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-7.js
  • process.env — Environment variable access in benchmark/comparison/superpowers-immune/round-8.js
  • process.env — Environment variable access in benchmark/comparison/superpowers/round-1.js
  • process.env — Environment variable access in benchmark/comparison/superpowers/round-2.js
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This tool is a hybrid adaptive memory system for AI agents, specifically designed for Claude Code. It learns from past interactions by remembering both positive best practices (cheatsheet) and negative patterns to avoid (immune/antibodies), using local semantic search to continuously improve future outputs.

Security Assessment
The overall risk is Low. The tool does not request any dangerous system permissions, execute shell commands, or contain hardcoded secrets. The automated scan flagged environment variable access and one instance of file system access, but these are safely isolated within benchmark and comparison testing scripts. The core application relies on local storage (SQLite and JSON files) and runs a small local WASM machine-learning model for embeddings rather than making external network requests to APIs.

Quality Assessment
The project is actively maintained, with its most recent code push happening today. It is properly licensed under the standard MIT license, and it shows a fair level of community engagement with 10 GitHub stars. The developer-facing documentation is highly detailed, clearly explaining the dual-memory architecture, local storage setup, and data deduplication logic.

Verdict
Safe to use.
SUMMARY

Hybrid adaptive memory system for Claude Code — Cheatsheet (positive patterns) + Immune (negative patterns)

README.md

Immune System v4.1 — Hybrid Adaptive Memory for AI Agents

Stars
License: MIT

A self-improving memory system that makes AI outputs better over time through two complementary memories:

  • Immune (antibodies) — Detects and prevents known errors (negative patterns)
  • Cheatsheet (strategies) — Injects proven best practices before generation (positive patterns)

Architecture

[User Request]
  --> Context search (recall past sessions via FTS4)
  --> Inject cheatsheet strategies (positive patterns)
  --> Generate output (with strategy context)
  --> Immune scan (detect known + new errors)
  --> Fix errors + learn new antibodies
  --> Detect + learn new winning strategies
  --> Score (0-100, domain-normalized)
  --> Session log (for future context recall)
  --> Flush pending patterns (before context compaction)

Key Features

Semantic Search (v4.1)

  • Embeddings — Local Xenova/all-MiniLM-L6-v2 model (384 dims, ~22MB, runs in WASM)
  • TF-IDF + Cosine Similarity — Sparse vector fallback when embeddings unavailable
  • Character Trigrams — Jaccard similarity for fuzzy matching
  • Hybrid Re-ranking — alpha * textual_similarity + (1-alpha) * heat_score
  • Auto-switch — Full-scan for small corpus (<200), FTS4 pre-filter for large corpus

Hot/Cold Tiering

Keeps context lean for optimal performance:

  • Hot — Active patterns: critical severity, seen >= 3 times, or recent (<30 days)
  • Cold — Dormant patterns: sent as one-line summaries, auto-reactivated on match

Dual Storage

  • SQLite (immune.sqlite) — FTS4 full-text search + structured queries
  • JSON (immune_memory.json / cheatsheet_memory.json) — Portable fallback

Deduplication

  • Embedding-based cosine similarity (threshold: 0.7)
  • Jaccard + longest common subsequence fallback (threshold: 0.55)
  • Quality gate: min 20 chars pattern, required fields enforced

Housekeeping

  • Smart archival of useless patterns (COLD + low engagement + >180 days)
  • Configurable limits (500 antibodies, 300 strategies, 50MB SQLite)
  • Freeze/unfreeze to pause aging during inactive periods

File Structure

immune/
  immune-adapter.js        # CLI adapter — all operations go through this
  sanitizer.js              # Input sanitization
  config.yaml               # Full configuration (thresholds, domains, limits)
  immune_memory.json        # Antibodies (79 entries)
  cheatsheet_memory.json    # Strategies (82 entries)
  migration_state.json      # Migration/phasing state
  analysis.json             # Pattern analysis data
  package.json              # Dependencies
  skill.md                  # Claude Code skill definition
  agents/
    immune-scan.md          # Scan agent instructions
  context/
    2026-03-29.md           # Session logs
    2026-04-01.md

CLI Commands

# Query
node immune-adapter.js get-antibodies --domains '["code"]' --tier hot --limit 15
node immune-adapter.js get-strategies --domains '["code"]' --query "security" --limit 10
node immune-adapter.js search --query "XSS injection" --type antibodies

# Add/Update
node immune-adapter.js add-antibody --json '{"id":"AB-001","pattern":"...","severity":"critical","correction":"..."}'
node immune-adapter.js update-antibody --id AB-001 --increment_seen

# Bulk
node immune-adapter.js flush-pending --json '{"antibodies":[...],"strategies":[...]}'
node immune-adapter.js import --file export.immune.json

# Maintenance
node immune-adapter.js index              # Rebuild FTS4 index
node immune-adapter.js stats              # Show counts and migration state
node immune-adapter.js housekeep          # Archive useless patterns
node immune-adapter.js integrity-check    # SQLite integrity check
node immune-adapter.js freeze             # Pause aging clocks
node immune-adapter.js unfreeze           # Resume aging clocks

# Testing
node immune-adapter.js similarity-test    # Run dedup test suite
node immune-adapter.js retrieval-test     # Run semantic retrieval tests
node immune-adapter.js check-duplicate --pattern "..." --type antibody

Domains

Patterns are tagged with domains for targeted retrieval:

Domain Keywords
code function, class, import, SQL, API, worker
fitness séries, reps, exercice, squat, programme
writing paragraphe, article, SEO, blog
research source, étude, analyse, hypothèse
strategy marché, compétiteur, ROI, revenue
webdesign CSS, HTML, responsive, CTA, UI
travel voyage, plage, hôtel, itinéraire, visa
_global Cross-domain patterns

Configuration

All tunable parameters are in config.yaml:

  • Re-ranking alpha (textual vs heat balance)
  • Deduplication thresholds (embedding: 0.7, Jaccard: 0.55)
  • Hot/Cold criteria
  • Housekeeping limits and archival rules
  • Domain keywords for auto-detection

Dependencies

  • sql.js — SQLite in WASM
  • @xenova/transformers — Local embedding model (auto-installed on first use)
  • proper-lockfile — Concurrency safety

License

MIT

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