Agent skill

flow-nexus-neural

Stars 27
Forks 6

Install this agent skill to your Project

npx add-skill https://github.com/DNYoussef/context-cascade/tree/main/skills/platforms/flow-nexus-neural

SKILL.md

/============================================================================/ /* FLOW-NEXUS-NEURAL SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/


name: flow-nexus-neural version: 1.0.0 description: | [assert|neutral] Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus [ground:given] [conf:0.95] [state:confirmed] category: ai-ml tags:

  • neural-networks
  • distributed-training
  • machine-learning
  • deep-learning
  • flow-nexus author: ruv cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute flow-nexus-neural workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic ai-ml processes"

/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/

[define|neutral] SKILL := { name: "flow-nexus-neural", category: "ai-ml", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/

[define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed]

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

/----------------------------------------------------------------------------/ /* S2 TRIGGER CONDITIONS / /----------------------------------------------------------------------------*/

[define|neutral] TRIGGER_POSITIVE := { keywords: ["flow-nexus-neural", "ai-ml", "workflow"], context: "user needs flow-nexus-neural capability" } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/

When NOT to Use This Skill

  • Local development without cloud infrastructure needs
  • Simple scripts that do not require sandboxed execution
  • Operations without distributed computing requirements
  • Tasks that can run on single-machine environments

Success Criteria

  • [assert|neutral] API response time: <200ms for sandbox creation [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Deployment success rate: >99% [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Sandbox startup time: <5s [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Network latency: <50ms between sandboxes [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Resource utilization: <80% CPU/memory per sandbox [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Uptime: >99.9% for production deployments [ground:acceptance-criteria] [conf:0.90] [state:provisional]

Edge Cases & Error Handling

  • Rate Limits: Flow Nexus API has request limits; implement queuing and backoff
  • Authentication Failures: Validate API tokens before operations; refresh expired tokens
  • Network Issues: Retry failed requests with exponential backoff (max 5 retries)
  • Quota Exhaustion: Monitor sandbox/compute quotas; alert before limits
  • Sandbox Timeouts: Set appropriate timeout values; clean up orphaned sandboxes
  • Deployment Failures: Implement rollback strategies; maintain previous working state

Guardrails & Safety

  • [assert|emphatic] NEVER: expose API keys or authentication tokens in code or logs [ground:policy] [conf:0.98] [state:confirmed]
  • [assert|neutral] ALWAYS: validate responses from Flow Nexus API before processing [ground:policy] [conf:0.98] [state:confirmed]
  • [assert|neutral] ALWAYS: implement timeout limits for long-running operations [ground:policy] [conf:0.98] [state:confirmed]
  • [assert|emphatic] NEVER: trust user input for sandbox commands without validation [ground:policy] [conf:0.98] [state:confirmed]
  • [assert|neutral] ALWAYS: monitor resource usage to prevent runaway processes [ground:policy] [conf:0.98] [state:confirmed]
  • [assert|neutral] ALWAYS: clean up sandboxes and resources after task completion [ground:policy] [conf:0.98] [state:confirmed]

Evidence-Based Validation

  • Verify platform health: Check Flow Nexus status endpoint before operations
  • Validate deployments: Test sandbox connectivity and functionality
  • Monitor costs: Track compute usage and spending against budgets
  • Test failure scenarios: Simulate network failures, timeouts, auth errors
  • Benchmark performance: Compare actual vs expected latency/throughput

Flow Nexus Neural Networks

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

Deploy, train, and manage neural networks in distributed E2B sandbox environments. Train custom models with multiple architectures (feedforward, LSTM, GAN, transformer) or use pre-built templates from the marketplace.

Prerequisites

bash
# Add Flow Nexus MCP server
claude mcp add flow-nexus npx flow-nexus@latest mcp start

# Register and login
npx flow-nexus@latest register
npx flow-nexus@latest login

Core Capabilities

1. Single-Node Neural Training

Train neural networks with custom architectures and configurations.

Available Architectures:

  • feedforward - Standard fully-connected networks
  • lstm - Long Short-Term Memory for sequences
  • gan - Generative Adversarial Networks
  • autoencoder - Dimensionality reduction
  • transformer - Attention-based models

Training Tiers:

  • nano - Minimal resources (fast, limited)
  • mini - Small models
  • small - Standard models
  • medium - Complex models
  • large - Large-scale training

Example: Train Custom Classifier

javascript
mcp__flow-nexus__neural_train({
  config: {
    architecture: {
      type: "feedforward",
      layers: [
        { type: "dense", units: 2

/*----------------------------------------------------------------------------*/
/* S4 SUCCESS CRITERIA                                                         */
/*----------------------------------------------------------------------------*/

[define|neutral] SUCCESS_CRITERIA := {
  primary: "Skill execution completes successfully",
  quality: "Output meets quality thresholds",
  verification: "Results validated against requirements"
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S5 MCP INTEGRATION                                                          */
/*----------------------------------------------------------------------------*/

[define|neutral] MCP_INTEGRATION := {
  memory_mcp: "Store execution results and patterns",
  tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"]
} [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S6 MEMORY NAMESPACE                                                         */
/*----------------------------------------------------------------------------*/

[define|neutral] MEMORY_NAMESPACE := {
  pattern: "skills/ai-ml/flow-nexus-neural/{project}/{timestamp}",
  store: ["executions", "decisions", "patterns"],
  retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]

[define|neutral] MEMORY_TAGGING := {
  WHO: "flow-nexus-neural-{session_id}",
  WHEN: "ISO8601_timestamp",
  PROJECT: "{project_name}",
  WHY: "skill-execution"
} [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S7 SKILL COMPLETION VERIFICATION                                            */
/*----------------------------------------------------------------------------*/

[direct|emphatic] COMPLETION_CHECKLIST := {
  agent_spawning: "Spawn agents via Task()",
  registry_validation: "Use registry agents only",
  todowrite_called: "Track progress with TodoWrite",
  work_delegation: "Delegate to specialized agents"
} [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S8 ABSOLUTE RULES                                                           */
/*----------------------------------------------------------------------------*/

[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* PROMISE                                                                     */
/*----------------------------------------------------------------------------*/

[commit|confident] <promise>FLOW_NEXUS_NEURAL_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]

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