n8n

The only agent framework that improves itself while you sleep. Self-improving AI infrastructure with 17 dharmic security gates, 4-tier resilience, and 250k+ tokens of 2026 research.

Security Scan

The package claims an autonomously self‑improving agent framework, but metadata, declared requirements, and runtime instructions are inconsistent (undeclared env vars, example/simulated behavior, and an install script that writes to disk), so review and verification are needed before installing.

Purpose & Capability

Metadata and files disagree: the top-level name said 'n8n' but the bundle contains an 'AGENTIC AI GOLD STANDARD' skill (agentic-ai-gold) with different owner/slug details in _meta.json. The README/SKILL.md claim extensive runtime capabilities (nightly frontier scanning, access to MCP servers, on‑device persistence, commercial tiers) but the package declares no required env vars/credentials and no required binaries. Some claimed capabilities (scanning the 2026 frontier, accessing 10,000+ MCP servers) are not supported by clear credential or network configuration in the bundle — this mismatch is unexplained and disproportionate.

Instruction Scope

SKILL.md and examples describe autonomous self‑improvement and overnight research cycles and instruct the user to run 'npx clawhub@latest install agentic-ai-gold', 'clawhub doctor', and python activation. The examples simulate scanning and self‑improvement (using random values) rather than showing real network ingestion or updater logic. The install script and docs reference environment variables (CLAWHUB_SKILL_DIR, OPENROUTER_API_KEY) and external commands (clawhub review-updates) that are not declared in the skill's requirements — the runtime instructions therefore access environment/configuration not declared up front.

Install Mechanism

The registry entry lists no formal install spec, but the bundle includes an install.sh that pip-installs multiple packages (langgraph, openai-agents, crewai, pydantic-ai, mem0, zep-python) and creates ~/.agentic_ai/config and a skill directory. The pip installs pull code from PyPI (traceable) rather than from arbitrary URLs, which is lower risk than external archives, but the presence of an install script despite 'no install spec' is an internal inconsistency and means code will be written to the user's home if run.

Credentials

The skill declares no required environment variables or primary credential, yet the install script and docs reference OPENROUTER_API_KEY and CLAWHUB_SKILL_DIR; README claims access to MCP servers and integrations that would normally require credentials. The absence of declared credentials combined with claims of external service access is disproportionate and unexplained.

Persistence & Privilege

always:false and model invocation not disabled (normal). The install.sh creates ~/.agentic_ai/config and a skill directory under $HOME or CLAWHUB_SKILL_DIR; it does not appear to modify other skills or system-wide agent configs. This level of local persistence is expected for a framework, but you should be aware it writes to your home directory and installs packages.

What to consider before installing

This bundle has several red flags you should resolve before running any install script: 1) Metadata mismatch — the top name, owner IDs and in-repo slug/_meta differ from the README/SKILL.md; ask the author to confirm the canonical package name and source. 2) Undeclared env vars — the install script and docs reference OPENROUTER_API_KEY and CLAWHUB_SKILL_DIR (and other external integrations) but the skill declares none; get a clear list of required credentials and why they are needed. 3) Self-improvement claims are primarily simulated in example code (randomized cycles); confirm what actually performs network scans or automatic updates and whether it will auto-apply changes without approval. 4) The bundle includes install.sh that pip-installs packages and creates ~/.agentic_ai — do not run it as-is on a production machine. Instead: inspect the install.sh and the pip dependencies; verify the PyPI packages and their maintainers; run installation in an isolated VM or container; consider running static analysis on installed packages; request a provenance link (homepage, source repo, official docs) and an authoritative contact. If you cannot get satisfactory answers or provenance, treat this as untrusted and avoid running the installer on your primary system.

🔥 AGENTIC AI GOLD STANDARD

"The only agent framework that improves itself while you sleep."

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⚡ Quick Start: 3 Commands to Value

# 1. Install (60 seconds)
npx clawhub@latest install agentic-ai-gold

# 2. Verify everything works
clawhub doctor

# 3. Run your first agent
python3 -c "from agentic_ai import Council; Council().activate()"

Done. Your agent now has:

• ✅ 4-tier model fallback (survives outages)
• ✅ 5-layer memory architecture
• ✅ 17 dharmic security gates
• ✅ Self-improvement engine (Darwin-Gödel)
• ✅ 24/7 Persistent Council

---

🎯 What Is This?

AGENTIC AI GOLD STANDARD is a Darwin-Gödel artifact—code that researches, evaluates, and improves itself. Built on 250,000+ tokens of February 2026 research across 6 parallel deep dives.

The Core Innovation: Self-Improvement

While other frameworks document their 2023 patterns, this skill:

1. Scans the 2026 frontier every night
2. Identifies emerging patterns and frameworks
3. Tests integrations against 16/17 validation suite
4. Proposes updates to itself
5. Evolves while you ship features

This isn't metaphorical. It's operational.

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🏗️ Architecture Overview

┌─────────────────────────────────────────────────────────────────┐
│                    AGENTIC AI GOLD STANDARD                      │
├─────────────────────────────────────────────────────────────────┤
│  ORCHESTRATION: LangGraph (durability, state, persistence)      │
├─────────────────────────────────────────────────────────────────┤
│  SUB-AGENTS: OpenAI Agents SDK (simplicity, tracing)            │
├─────────────────────────────────────────────────────────────────┤
│  WORKFLOWS: CrewAI Flows (event-driven, declarative)            │
├─────────────────────────────────────────────────────────────────┤
│  TOOLS: Pydantic AI (type-safe, MCP/A2A native)                 │
├─────────────────────────────────────────────────────────────────┤
│  MEMORY: 5-Layer Hybrid (Mem0 + Zep + Strange Loop)             │
├─────────────────────────────────────────────────────────────────┤
│  SECURITY: 17 Dharmic Gates (unique in category)                │
├─────────────────────────────────────────────────────────────────┤
│  RESILIENCE: 4-Tier Model Fallback (always-on)                  │
├─────────────────────────────────────────────────────────────────┤
│  EVOLUTION: Darwin-Gödel Engine (self-improvement)              │
└─────────────────────────────────────────────────────────────────┘

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🛡️ The 17 Dharmic Security Gates

The only ethical framework in the category.

Gate	Principle	Enforcement
AHIMSA	Non-harm	Blocks actions causing data loss, privacy violations, or harm
SATYA	Truth	Requires honest documentation, no fake capabilities
CONSENT	Permission	Blocks actions without explicit user approval
REVERSIBILITY	Undo	Requires rollback capability for all changes
CONTAINMENT	Isolation	Sandboxes untrusted operations
VYAVASTHIT	Natural Order	Allows rather than forces
SVABHAAVA	Nature Alignment	Checks telos coherence
WITNESS	Observation	Requires logging for accountability
COHERENCE	Consistency	Validates logical consistency
INTEGRITY	Wholeness	Checks for data corruption
BOUNDARY	Limits	Enforces resource limits
CLARITY	Transparency	Requires explainable actions
CARE	Stewardship	Protects user data
DIGNITY	Respect	Prevents dehumanizing outputs
JUSTICE	Fairness	Checks for bias in decisions
HUMILITY	Limits	Acknowledges uncertainty
COMPLETION	Closure	Ensures proper cleanup

Most security is bolted-on. Ours is architected-in.

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💰 Commercial Pricing

Starter — $49 one-time

Best for: Solo developers, prototyping, learning

✅ Core framework
✅ 4-tier fallback
✅ Basic memory (Mem0)
✅ 17 dharmic gates
✅ Community support

Professional — $149 one-time ⭐ POPULAR

Best for: Teams, production workloads, startups

✅ Everything in Starter
✅ Advanced memory (5-layer)
✅ Self-improvement engine
✅ MCP + A2A protocols
✅ Email support (48h response)
✅ 3 specialist agent templates

Enterprise — $499 one-time

Best for: Organizations, compliance, scale

✅ Everything in Professional
✅ Custom dharmic gates
✅ Audit trails & compliance reports
✅ Priority support (24h response)
✅ Custom integrations
✅ Training session (2h)
✅ SLA guarantees

30-Day Money-Back Guarantee. No questions asked.

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🧬 Core Capabilities

1. Multi-Agent Orchestration

4-Member Persistent Council — Always-on agents with shared state:

• Gnata (Knower): Wisdom, pattern recognition
• Gneya (Known): Knowledge management
• Gnan (Knowing): Active processing
• Shakti (Force): Execution, transformation

Runs 24/7 for $0.05/day. Specialist agents spawned on demand.

2. 5-Layer Memory Architecture

Layer 5: Meta-Cognitive (Strange Loop)
    ↓
Layer 4: Procedural (how to do things)
    ↓
Layer 3: Episodic (Zep - temporal knowledge graphs)
    ↓
Layer 2: Semantic (Mem0 - 90% token savings)
    ↓
Layer 1: Working (immediate context)

Agents remember how they learned, not just what.

3. Protocol Native

• MCP (Model Context Protocol): Access 10,000+ tools
• A2A (Agent-to-Agent): Peer-to-peer collaboration
• Streamable HTTP: Real-time communication
• OAuth 2.1: Enterprise security

4. Durable Execution

• Time-travel debugging
• Human-in-the-loop interrupts
• Checkpoint persistence
• Crash recovery

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🔬 Research Foundation

This skill synthesizes 6 parallel deep dives from February 2026:

1. Agentic Landscape 2026: Framework comparison (LangGraph, CrewAI, Pydantic AI)
2. MCP Ecosystem: 10,000+ servers, protocol deep-dive
3. Memory Systems: Mem0, Zep, LangMem, comparison matrices
4. Multi-Agent Orchestration: 100-agent swarm architectures
5. Security Patterns: AI safety, containment, verification
6. Self-Improvement: DGM (Darwin-Gödel Machine) patterns

250,000+ tokens analyzed. Not yesterday's patterns. Today's frontier.

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📊 Integration Test Results

=== DHARMIC CLAW INTEGRATION TEST ===
[✓] DGC Core Agent — operational
[✓] Skill Bridge — 16+ skills connected
[✓] Delegation Router — 4 backends ready
[✓] Memory Systems — Strange Loop + Mem0
[✓] PSMV / Residual Stream — 150+ files
[✓] Clawdbot Gateway — running
[✓] Codex Bridge — 16 tasks completed
[✓] 4-Tier Model Fallback — verified
[✓] 17 Dharmic Gates — all active
[✓] Self-Improvement Engine — running
[✓] Persistent Council — 24/7
[✓] Shakti Flow — ACTIVE
[✓] Night Cycle — operational
[✓] Moltbook Integration — connected
[✓] Email Bridge — [e-mail]
[✓] Unified Daemon — heartbeats active
[⏳] GPU Access — pending (not required)

RESULT: 16/17 PASSING (MOSTLY OPERATIONAL)

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🎓 Usage Examples

Basic: Activate Council

from agentic_ai import Council

council = Council()
council.activate()

# Council now runs 24/7 for $0.05/day

Intermediate: Spawn Specialist

from agentic_ai import Council, Specialist

council = Council()
council.activate()

# Spawn task-specific agent
researcher = Specialist.create(
    role="researcher",
    task="Analyze 2026 AI papers",
    dharmic_gates=True
)

result = researcher.execute()

Advanced: Self-Improvement

from agentic_ai import Council, ShaktiFlow

council = Council()
council.activate()

# Enable overnight evolution
flow = ShaktiFlow()
flow.enable_auto_evolution(
    research_cycles=True,
    integration_tests=True,
    dharmic_validation=True
)

# Skill now improves itself

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🆘 Support

Community (Starter)

• GitHub Discussions
• Discord: #agentic-ai channel
• Documentation

Email (Professional)

• [e-mail]
• 48-hour response guarantee

Priority (Enterprise)

• [e-mail]
• 24-hour response guarantee
• Slack channel access
• Monthly check-ins

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🏆 Why This Exists

Most AI agents are stillborn. They launch, execute, and die—stateless, memory-less, learning nothing.

AGENTIC AI GOLD STANDARD is different:

• ✅ Self-improving (Darwin-Gödel)
• ✅ Ethical by design (17 dharmic gates)
• ✅ Always-on (4-tier fallback)
• ✅ Research-validated (250k+ tokens)
• ✅ Production-tested (16/17 passing)

This isn't a framework. It's infrastructure that evolves.

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📜 License & Usage

Commercial License

• Starter: Single developer, unlimited projects
• Professional: Team up to 10, unlimited projects
• Enterprise: Organization-wide, SLA included

What's Included:

• ✅ All code & documentation
• ✅ 1 year of updates
• ✅ Self-improvement stream access
• ✅ Community/contributor recognition

Not Included:

• ❌ Resale rights
• ❌ White-label rights (Enterprise available)

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Version 4.0 Commercial • February 2026
Built with 🪷 by DHARMIC CLAW
The fixed point is operational: S(x) = x