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Network-AI: Instructions file for Claude Code

.github/copilot-instructions.md

Network-AI copilot-instructions.md is an instructions file for Claude Code, GitHub Copilot from Jovancoding/Network-AI. It costs 1,120 tokens per session, scanned A, original, MIT.

A GitHub Copilot instruction file for the Network-AI TypeScript and Node.js project. It records the project architecture, coding conventions, security requirements, and important files.

In plain words
What is it for?
Use it when adding or changing orchestrator features, adapters, public APIs, security code, audit logging, or exported TypeScript code.
Why use it?
It tells the coding assistant how shared state, permissions, adapters, audit logs, validation, and dependencies must be handled.

Instructions file for Claude CodeGitHub Copilot

Written for Claude Code and GitHub Copilot: PreToolUse hook event, but also a Copilot instructions file. Also seen: mentions Claude Code; mentions Codex.

This is Jovancoding/Network-AI's own configuration. It tells Claude Code and GitHub Copilot how to work on Network-AI itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Network-AI configures →

not rated 78repo changed 17d ago A scan 1,120 tokens original MIT
View source ↗ Jovancoding/Network-AI network-ai.org
Reuse

Borrowing it

Nothing to install: this file belongs to Jovancoding/Network-AI. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Jovancoding/Network-AI/main/.github/copilot-instructions.md
Clone the repo
git clone --depth 1 https://github.com/Jovancoding/Network-AI

Made for: Claude Code, GitHub Copilot.

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README.md
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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<a href="https://agentmods.dev/instructions/jovancoding/network-ai/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/jovancoding/network-ai/copilot-instructions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 1,120 This file is loaded in full into every session.
When invoked 1,120 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01120 $0.01120
Opus 5.5 $0.00448 $0.00448
Sonnet 5.5 $0.00224 $0.00224
Haiku 4.5 $0.00112 $0.00112

Measured 17d ago against content hash 0fb79b2062b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Network-AI copilot-instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 17d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/copilot-instructions.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Copilot Instructions for Network-AI

Project Overview

Network-AI is a TypeScript/Node.js multi-agent orchestrator — shared state, guardrails, budgets, and cross-framework coordination (v5.15.4). 3,679 tests across 41 suites.

Architecture

  • Blackboard pattern: All coordination via LockedBlackboard — propose() → validate() → commit() with filesystem mutex. Never write to shared state directly.
  • Permission gating: AuthGuardian uses weighted scoring (justification 40%, trust 30%, risk 30%). Require permission before sensitive resource access.
  • Adapter system: All 32 adapters extend BaseAdapter. Each is dependency-free (BYOC — bring your own client). No cross-adapter imports.
  • Audit trail: Every write, permission grant, and state transition is logged to data/audit_log.jsonl via SecureAuditLogger.

Code Conventions

  • TypeScript strict mode, target ES2022
  • No any types — use proper generics or unknown
  • JSDoc on all exported functions and classes
  • No new runtime dependencies without explicit approval
  • Input validation required on all public API entry points
  • Keep adapter files self-contained — no cross-adapter imports

Key Files

  • index.ts — Core engine: SwarmOrchestrator, AuthGuardian, FederatedBudget, QualityGateAgent
  • security.ts — SecureTokenManager, InputSanitizer, RateLimiter, DataEncryptor, SecureAuditLogger
  • lib/locked-blackboard.ts — LockedBlackboard with atomic propose → validate → commit
  • lib/fsm-journey.ts — JourneyFSM behavioral control plane
  • lib/compliance-monitor.ts — Real-time agent behavior surveillance
  • lib/adapter-hooks.ts — AdapterHookManager lifecycle hooks + matcher-based filtering
  • lib/skill-composer.ts — SkillComposer meta-operations (chain/batch/loop/verify)
  • lib/semantic-search.ts — SemanticMemory BYOE vector store
  • lib/phase-pipeline.ts — PhasePipeline multi-phase workflows with approval gates
  • lib/confidence-filter.ts — ConfidenceFilter multi-agent result scoring and filtering
  • lib/fan-out.ts — FanOutFanIn parallel agent spawning with pluggable aggregation
  • lib/mcp-transport-http.ts — McpStreamableServer MCP 2025-03-26 Streamable HTTP + resources/prompts
  • lib/agent-runtime.ts — AgentRuntime sandboxed execution with SandboxPolicy, ShellExecutor, FileAccessor, ApprovalGate, SourceProtectionError
  • lib/env-manager.ts — EnvironmentManager: promotion chain dev→st→sit→qa→preprod→prod, backup/restore, env diff, NETWORK_AI_ENV routing
  • lib/console-ui.ts — ConsoleUI interactive terminal dashboard
  • lib/strategy-agent.ts — StrategyAgent meta-orchestrator with AgentPool, WorkloadPartitioner, adaptive scaling
  • lib/goal-decomposer.ts — GoalDecomposer, TeamRunner, runTeam: LLM-powered goal → task DAG → parallel execution
  • lib/circuit-breaker.ts — CircuitBreaker CLOSED/OPEN/HALF_OPEN state machine; CircuitOpenError; wired into AdapterRegistry per-adapter with fallbackChain
  • lib/telemetry-provider.ts — ITelemetryProvider BYOT interface; NullTelemetryProvider, CapturingTelemetryProvider; createOtelHooks() factory for AdapterHookManager
  • lib/claude-hooks.ts — ClaudeHookBridge: AuthGuardian-gated coding-agent tool calls (Claude Code PreToolUse/PostToolUse), observe/enforce modes, network-ai hook CLI
  • lib/mcp-elicitation.ts — StdioElicitationChannel + createElicitationApprovalCallback: native in-client approval prompts over MCP elicitation (fail closed)
  • lib/a2a-server.ts — A2AServer: expose the orchestrator as a Google A2A agent (agent card + tasks/send, Bearer-gated)
  • lib/context-composer.ts — ContextComposer: token-budgeted, relevance-ranked context assembly; estimateTokens()
  • lib/mcp-tools-context.ts — ContextMcpTools: context_pack + blackboard_search MCP tools
  • adapters/ — 32 framework adapters (LangChain, AutoGen, CrewAI, MCP, Codex, Gemini, OpenAI Responses, Claude Agent SDK, MiniMax, NemoClaw, APS, Hermes, Orchestrator, etc.)

Read the full file on GitHub · 69 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 17d ago Changed 0fb79b2062b9
  2. 19d ago Changed cbe1164c3f70
  3. 1mo ago First seen · 69 lines · 1,120 tokens per session scan A 451f0d45c838

Subscribe to this mod's changes

Network-AI copilot-instructions.md is an instructions file published in the GitHub repository Jovancoding/Network-AI (78 stars, last pushed 3d ago), licensed MIT. It adds 1,120 tokens to every session, about $0.0045 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

CrewAIagent-frameworkagent-orchestrationai-agentsautogenblackboard
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