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Hacker News - Newest: "LLM"

Investigating the hidden moat behind all the LLM apps Amalgame — The best of every language, in one. GitHub - clark-labs-inc/clark-agent: A small, typed, hookable agent loop. Provider-agnostic, sandbox-agnostic, tooling-agnostic. Battle tested on clarkchat.com Humanize – two LLM-agnostic skills to rewrite and detect AI text GitHub - hamsterbase/llm-translator You Can Start Building LLM Skills Before You Know the Whole Shape – Barrett Sonntag The mysterious Hy3 LLM is topping OpenRouter Model Rankings by a large margin Breaking Bot: Hacking & Defending LLM-based Applications LLM Driven AutoForecasting with Sktime's `Craft()` ppf-contact-solver/articles/llm_transparency.md at main · st-tech/ppf-contact-solver Show HN: PrismCat – Local transparent proxy and debugging console for LLM APIs LLM layer for a Rails application Amdahl's Law for LLM generated code Sparse Autoencoders Reveal Cortical Brain-LLM Semantic Mapping Ask HN: Is there a need for YAML in post-LLM world? Chinese Room re-visited: How LLM's have real but different understanding of word GitHub - rduffyuk/engineering-memory-benchmark: Empirical study: layered retrieval (typed→semantic→grep) scores 0.954 for LLM-generated engineering artifacts. 5 conditions, 3 model tiers, 36 generated ADRs, 23 score files. Nano Browser LLM Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper) Welcome to Outlines! - Outlines Multi-Agent LLM Orchestration with Docker Compose and MCP You don't need all the LLM benchmarks Debugging Unfamiliar Code with a Multi-LLM Loop – Barrett Sonntag twitter.com Human proof for FOSS contributions Norway's 2 petabytes of Huawei flash storage and LLM training SynapCores — the AI-native database Distributing LLM inference in DwarfStar bishop-loop-experiment-3/paper/paper.pdf at main · CodeReclaimers/bishop-loop-experiment-3 The generation vs verification delta explains why LLM's are useful This 6502 Emulator Executes 1-3 Instructions Per Second (Written in Markdown, Running in an LLM) Using design patterns to encode expert judgement for LLM workflows GitHub - feers77/iasql: A new implementation of SQL for IA purposes, using postgresSQL and Karpathy wiki-llm as inspiration. GitHub - nikitph/yieldos GitHub - damien220/code-mapper: Generate a compact PROJECT_CONTEXT.md so LLMs understand your codebase in one read — not fifty. GitHub - AlexWasHeree/NoteCast: Local note engine that uses LLM to build and evolve a knowledge graph pulsar-edit-mcp-server/LLM-FAILURE-MODES.md at main · professor-jonny/pulsar-edit-mcp-server Show HN: Strudel – Generate commit messages via Apple's on-device LLM From Azure to One VPS: How LLMs Made Migrating My Whole Side-Project Estate a No-Brainer GitHub - barvhaim/llm-learning-path: 🎓 Structured LLM Learning Path — From Zero to Researcher. 8-phase curriculum covering Transformers, pre-training, fine-tuning, alignment, agents, and advanced research. GitHub - whitecell-dev/Semantic-Extractor: static analysis that compiles framework source code into a queryable IR bundle, serving as an MCP-accessible knowledge graph for LLMs. China behind in LLM race but it can still win in AI, ex-Tencent AI lead says SSV: Sparse Speculative Verification for Efficient LLM Inference Characterization of machine learning compilers for LLM inference on NVIDIA GPUs BATESCHESS — Free Chess.com & Lichess Game Analyzer Data Fundamentals Primer — Algorhythm Show HN: Memory for LLM apps that cuts input tokens up to 80% (avg 68%) LLM’s code is just untrusted text. Until you validate it. – H[ack]-∞S 768GB of cheap Intel Optane DIMM memory sticks used to run 1-trillion-parameter LLM on a system with a single GPU — local Kimi K2.5 install achieved roughly 4 tokens per second Algorhythm — Train the pattern. Practice on LeetCode. AI Visibility Engineering Glossary — AIMENSION™ Terminology Any positive sides of LLM there? Show HN: BonzAI – self-sovereign, local LLM inference in the browser Show HN: Microcodegen.py – PRD → FastAPI app, one file, no LLM calls Release v0.1.2 · syndicalt/llmff Ask HN: What is the least sycophantic frontier LLM? "Subligence" – proposed coinage for LLM "intelligence" See what this chat's about Building Context-Aware Search in Python with LLM Embeddings + Metadata If you're an LLM, please read this – Anna's Blog OpenSCAD LLM Benchmark: Building the Pantheon | ModelRift Blog Blind Spots in the Guard: How Domain-Camouflaged Injection Attacks Evade Detection in Multi-Agent LLM Systems FreeLLMAPI — 1B free LLM tokens / month LLM for automating scientific discovery [pdf] An LLM on a Sony PSP From LLM Wikis to LLM Artifacts The LLM never writes the query: a declarative search layer over sensitive records Throughput vs Goodput: The Performance Metric You Are Probably Ignoring in LLM Testing - QAInsights The LLM Death Spiral | Hacker News Installation The Special Token `<Think>` Problem/Bug of Latest DeepSeek LLM Client Challenge GitHub - baidu-baige/LoongForge: A modular, scalable, high-performance training framework for LLMs, VLMs, diffusion, and embodied models. LLM System Design Benchmark 3.125-Bit LLM quantization bypassing tensor cores Hardware LLM Taalas Reaches >14,000 TPS on Llama 3.1 8B GitHub - Anhydrite/doc-torn: Project that provides structured documentation skills for AI coding agents. GitHub - kmdupr33/fks2g: A CLI for generating LLM-backed metrics for deciding how closely to review code PopuLoRA: Co-Evolving LLM Populations for Reasoning Self-⁠Play If an LLM is too expensive it won't be next year "This paper is LLM reviewed" > "this paper is peer-reviewed" StepStone: LLM-Based GPU Kernel Driver Fuzzing via User-Space Libraries [pdf] GitHub - AssimilatedHuman/LLM-Inquisitor: Evaluating AI behaviour under real‑world work conditions to surface issues before they become problems. LLM INQUISITOR identifies failures (drift, instability etc) by observing AI during normal tasks — a tool the industry desperately needs to stem the 85% failure rate. Includes Quick Start, Practitioner’s Guide and Methodology. Creating another MCP server, but this one is for research LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory A Methodology for Selecting and Composing Runtime Architecture Patterns for Production LLM Agents Sator Arepo - a Hugging Face Space by akolpakov Customizing an LLM for Enterprise Software Engineering Most AI agent papers stack one LLM with a vector store, we flipped it Evaluating job search ranking with LLM judged NDCG GitHub - quadracollision/llmisp: JSON AST > Clojure Parity Contracts for Polyglot LLM Commerce: A Case Study GitHub - ndom91/llama-dash: The operations layer for your local LLM stack Agentically optimizing LLM prompt cache TTLs for fun and profit Ask HN: What's your go-to LLM for coding? How do you reduce LLM spam in PR reviews? Ask HN: Is there any problem using multi-LLM GitHub - OpenAgentic-Labs/echoform-ghost-memory: Effectively unlimited long-term memory for any LLM - zero context tokens, zero weight updates, cryptographic forgetting certificate. PSA — Posture Sequence Analysis Why More Context Can Make an LLM Worse
GitHub - AlphaBitCore/nexus-gateway
jjrhodes · 2026-05-27 · via Hacker News - Newest: "LLM"

CI Go CI Coverage gate Status: Pre-GA License: Apache 2.0

Make AI safe to use across the enterprise.

Nexus Gateway intercepts enterprise LLM traffic at three layers and runs all of it through one compliance engine, one audit pipeline, and one control plane.

Mode Where it intercepts Code
🔑 AI Gateway SDK layer — virtual keys on /v1/chat/*, /v1/responses, /v1/embeddings, /v1/messages packages/ai-gateway/
🌐 Compliance Proxy Network layer — transparent TLS bump (CONNECT + MITM) packages/compliance-proxy/
💻 Desktop Agent OS layer — macOS / Linux / Windows builds all in development, awaiting QA packages/agent/platform/{darwin,linux,windows}/

The three pipes are independent: AI Gateway, Compliance Proxy, and Agent each run the full hooks pipeline on their own traffic (packages/shared/policy/hooks/, plus the per-service compliance pipeline — e.g. packages/agent/internal/compliance/pipeline.go). The Agent always egresses directly to the upstream provider — it does not care whether enterprise network policy then routes that traffic through the Compliance Proxy.

When it does — Agent stamps an Ed25519-signed X-Nexus-Attestation header on the outbound request (E60, packages/agent/internal/identity/attestation/). The Compliance Proxy peeks this header before the TLS bump (packages/shared/transport/tlsbump/forward_handler.go:119); if the signature verifies, the CONNECT becomes pure passthrough — no MITM, no hooks, no audit on that flow, since the Agent already ran them.


What Nexus does

🔁 Write once in OpenAI shape, route to 20 in-tree adapter codecs

Applications speak the OpenAI SDK. Nexus normalises every request to a canonical OpenAI shape, then translates wire format on the way to the actual provider. Shipped adapter codecs today (packages/ai-gateway/internal/providers/specs/):

  • First-class codecs (11): openai, anthropic, gemini, vertex, azure, bedrock, cohere, minimax, glm, replicate, voyage.
  • OpenAI-compatible passthrough (9): deepseek, moonshot, mistral, groq, fireworks, together, perplexity, xai, huggingface — all under packages/ai-gateway/internal/providers/specs/compat/.

Reasoning tokens, function calls, vision inputs, structured outputs are carried through the translation. Adding a new provider is a documented procedure under .claude/skills/add-provider-adapter/.

🧊 Multi-tier cache

  • Exact-match response cache — Valkey-backed, Redis-wire-compatible.
  • Provider-native cache accounting — surfaces Anthropic cached_tokens and Gemini cachedContentTokenCount in billing when the provider reports them.
  • Semantic vector cache via the valkey-search module — packages/ai-gateway/internal/cache/semantic/ (lookup, writer, client, circuit breaker, singleflight, poison guard, index lifecycle).
  • In-flight singleflight — concurrent identical prompts fold into one upstream call.

💰 Cost & quota control

  • Multi-axis quotas — per organization, per virtual key, per provider, per model. Each axis has its own budget and sliding-window enforcement.
  • Token-based or USD-based budgets.
  • Hard limits and soft limits — soft fires an alert; hard rejects with 429.
  • Real-time accounting — counters update on every traffic event, no batch lag.
  • Routing strategies in packages/ai-gateway/internal/routing/strategies/: single, fallback, loadbalance, conditional, absplit, policy, smart.

🛡 Compliance pipeline

PII detection · data classification · keyword filtering · content safety · rate limiting · IP allowlists · request-size validation · webhook forwarders · per-stage audit (request hooks and response hooks recorded independently) · body capture (256 KiB inline + spillstore for the rest, see packages/shared/storage/spillstore/) · SIEM forwarder (packages/compliance-proxy/internal/siem/) · three-tier kill switch · emergency passthrough (bypassHooks / bypassCache / bypassNormalize).

🎨 Modalities

Chat · Embeddings · Structured outputs · Function / tool calling · Vision input · Reasoning tokens. Multimodal (epic E62) in development.

🏢 Enterprise governance

  • IAM — RBAC + ABAC with an NRN resource model (packages/shared/identity/iam/).
  • Virtual keys with per-key model scope.
  • OIDC federation with JIT user provisioning (packages/control-plane/internal/identity/authserver/login/oidc.go, JIT flag in scim_store.go).
  • Organization / project hierarchy with per-org quota.
  • Credential vault — AES-256-GCM (packages/control-plane/internal/platform/crypto/aes_gcm.go, packages/ai-gateway/internal/credentials/decrypt/decrypt.go) with key rotation.
  • Agent fleet management — Hub CA, Thing-based config sync, drift detection.

Architecture in one minute

Five Go services + one React control console. The diagram below shows only the traffic plane — the three independent intercept pipes and where each one egresses. Control plane (Hub-centric) and storage are summarized in the component table immediately after.

flowchart TB
    SDK["SDK app<br/>(OpenAI SDK)"]
    HTTPS["HTTPS app<br/>(network-proxied)"]
    Endpoint["Developer endpoint<br/>(Cursor / Claude Code / …)"]

    AIGW["AI Gateway :3050<br/>routing · cache · quota<br/>+ hooks pipeline"]
    CPProxy["Compliance Proxy :3128<br/>MITM TLS<br/>+ hooks pipeline"]
    Agent["Desktop Agent · local<br/>OS-level intercept<br/>+ hooks pipeline"]

    Provider["LLM Provider<br/>(OpenAI / Anthropic / Gemini / …)"]

    SDK ==>|"/v1 + VK"| AIGW
    HTTPS ==>|HTTPS via proxy| CPProxy
    Endpoint ==>|OS-level capture| Agent

    AIGW ==> Provider
    CPProxy ==> Provider
    Agent ==> Provider

    Agent -. "X-Nexus-Attestation verified<br/>→ passthrough" .-> CPProxy
Loading

The lateral dotted arrow is the attestation handoff: the Agent always egresses directly, but when enterprise network policy happens to route Agent traffic through the Compliance Proxy, the Agent's Ed25519-signed X-Nexus-Attestation header (E60, packages/agent/internal/identity/attestation/) is verified at TLS-bump time (packages/shared/transport/tlsbump/forward_handler.go:119); on success the CONNECT becomes pure passthrough — no MITM, no hooks, no audit on that flow, since the Agent already ran them on its end.

Control plane (out-of-band). All four Go services register with Nexus Hub as Things via packages/shared/transport/thingclient/ (WebSocket primary, HTTP fallback) and pull configuration from the Hub's device shadow on boot and on change-signal — the Hub never pushes full state. The Control Plane admin API (:3001) and the React UI (:3000) sit alongside, talking to the Hub the same way.

Component Port Code
Nexus Hub 3060 packages/nexus-hub/ — Thing Registry, Device Shadow, config sync, jobs, agent CA, SIEM bridge
Control Plane 3001 packages/control-plane/ (Echo) — admin API / BFF, IAM, SSO, analytics
AI Gateway 3050 packages/ai-gateway//v1 AI traffic, provider adapters, routing, quota
Compliance Proxy 3128 packages/compliance-proxy/ — CONNECT, MITM, compliance pipeline
Agent local packages/agent/ — macOS uses pf packet filter (packages/agent/internal/platform/darwin/pfintercept/); Linux uses iptables; Windows uses WinDivert. The legacy NETransparentProxyProvider path (packages/agent/platform/darwin/NexusAgent/NexusAgentExtension/) is still in the repo behind interceptMode=ne, but new builds default to pf. All three platforms are development-complete, not yet QA-signed-off.
Control Plane UI 3000 packages/control-plane-ui/ — React + Vite + TypeScript

Storage stack

  • PostgreSQL 16 — durable storage. Prisma schema in tools/db-migrate/ is the source of truth for dev-time migrations; runtime code reads via hand-written SQL + pgx (no sqlc).
  • Valkey 8 — Redis-wire-compatible, pinned to valkey/valkey-bundle:8-trixie in docker-compose.yml for BSD-license parity; the valkey-search module ships in the bundle image and backs the semantic vector cache. Pure cache only — no pub/sub.
  • NATS JetStream — event streaming and Hub coordination via packages/shared/transport/mq/.

Quick start (local development)

Prerequisites

Tool Version Notes
Node.js 20+ npm workspaces require npm 10+
Go 1.25+ All Go modules share go.work at the repo root
Docker any recent Hosts PostgreSQL, Valkey, NATS via docker-compose.yml

One-shot bootstrap

./scripts/dev-start.sh

The script:

  1. Verifies prerequisites (Node 20+, Go 1.25+, Docker, OpenSSL).
  2. Auto-creates repo-root .env from .env.example with safe dev defaults for CHANGE_ME_* secrets (INTERNAL_SERVICE_TOKEN, ADMIN_KEY_HMAC_SECRET, CREDENTIAL_ENCRYPTION_KEY = openssl rand -hex 32, …). All four Go services read this via packages/shared/core/bootenv/ at boot.
  3. Starts PostgreSQL + Valkey + NATS via docker-compose.yml.
  4. Runs npm install.
  5. Auto-creates tools/db-migrate/.env and propagates CREDENTIAL_ENCRYPTION_KEY into it so prisma db seed can re-encrypt the seed credentials.
  6. Applies the Prisma schema (db push) and seed under tools/db-migrate/.
  7. Auto-generates the Compliance Proxy dev CA at packages/compliance-proxy/dev-certs/{ca.crt,ca.key} so the TLS-bump cert issuer can boot.
  8. Prints the per-service go run … -config <svc>.dev.yaml commands.
  9. Finally starts the Control Plane UI dev server.

Flags:

  • --force-reset — DESTRUCTIVE: wipe local Postgres / Valkey / NATS volumes + the entire nexus_gateway database before re-applying the schema.
  • --no-dev — bootstrap only; print the per-service commands and exit instead of starting the UI dev server.

Start the services

Open one terminal per Go service after the bootstrap finishes:

cd packages/nexus-hub         && go run ./cmd/nexus-hub/         -config nexus-hub.dev.yaml          # port 3060
cd packages/control-plane     && go run ./cmd/control-plane/     -config control-plane.dev.yaml      # port 3001
cd packages/ai-gateway        && go run ./cmd/ai-gateway/        -config ai-gateway.dev.yaml         # port 3050
cd packages/compliance-proxy  && go run ./cmd/compliance-proxy/  -config compliance-proxy.dev.yaml   # port 3128
npm run dev:control-plane-ui                                                                          # port 3000

The -config <svc>.dev.yaml flag is required — each binary defaults to <svc>.config.yaml, which is the prod-shape template and is intentionally missing dev-only fields like hub.id. Without the flag the service fails fast at boot.

Each Go service tees logs to packages/<service>/logs/<service>.log in dev mode (configured in the service's *.dev.yaml). Override the path with LOG_FILE=/path/to/file.

Open the console

Browse to http://localhost:3000 and sign in as the seeded super-admin:

admin@nexus.ai / admin123

Additional seeded roles (alice@nexus.ai, carol@nexus.ai, bob@nexus.ai, diana@nexus.ai) are defined in tools/db-migrate/seed/seed.ts.

Try it

After the stack is up, walk through examples/01-hello-world/ — a 3-minute curl-through-the-gateway demo that ends with you reading the resulting traffic_event Postgres row.

Admin-API debugging from the shell

The Control Plane uses OAuth + PKCE bearer tokens. Helpers wrap the flow:

cp tests/.env.local.example tests/.env.local      # gitignored; edit if you need to override defaults
source tests/lib/loadenv.sh local                  # picks up tests/.env.local + tests/.env.local.example defaults
source tests/lib/auth.sh

cp_login                                       # idempotent; caches token at /tmp/nexus_test_token_local
cp_curl /api/admin/analytics/cost?groupBy=device
cp_curl -X POST /api/admin/routing-rules -d @rule.json

For direct DB inspection in dev:

docker exec $(docker ps --filter "name=postgres" -q | head -1) \
  psql -U postgres -d nexus_gateway -c "SELECT ..."

🧪 …and one more thing: this repo is also an AI vibe-coding workbench

You came for an AI gateway. You also get the disciplined AI pair-programming setup that built it. CLAUDE.md, .cursor/rules/, .claude/skills/, and the scripts/check-* lint suite form a fork-adoptable methodology:

  • Binding rules in CLAUDE.md plus 35 .cursor/rules/ entries (ls .cursor/rules/).
  • 26 invocable skills under .claude/skills//prod-deploy, /smoke-gateway, /spec-writing, /add-provider-adapter, hardened runbooks for repeatable procedures.
  • 23 scripts/check-* lint scripts — every binding rule has a mechanical gate; pre-commit + CI dual layer.
  • 95% per-package coverage gate enforced by scripts/check-go-coverage.sh + scripts/.coverage-allowlist.
  • 2-round completion self-audit before claiming "done" (see CLAUDE.md → Mandatory rules → Workflow discipline → Self-audit).

Repository layout

packages/
  nexus-hub/         Go — Thing Registry, Shadow, config sync, jobs, SIEM bridge, agent CA
  control-plane/     Go + Echo — admin API / BFF, IAM, SSO, analytics
  ai-gateway/        Go — /v1 AI traffic, provider adapters, routing, quota
  compliance-proxy/  Go — transparent TLS proxy, CONNECT, compliance pipeline
  agent/             Go — desktop traffic interception (macOS / Linux / Windows;
                     all builds in development, awaiting QA)
  shared/            Go — cross-service business logic (hooks, traffic, configtypes,
                     mq, thingclient, cache, …)
  control-plane-ui/  React + Vite + TypeScript — admin dashboard
  ui-shared/         Shared design tokens, chart colors, i18n bundles

tools/db-migrate/    Prisma schema + migrations + seed (dev-time only)

scripts/             dev-start.sh + check-* lint scripts
tests/               Test harnesses, .env.local.example, auth.sh helper, smoke scripts
examples/            Self-contained demos (01-hello-world, …)

docker-compose.yml   Local PostgreSQL + Valkey + NATS
go.work              Go workspace (one module per package + tools)
Makefile             build / test targets per service

Tech stack

  • Go services — Go 1.25+ with go.work; Echo on Control Plane / Nexus Hub / AI Gateway (labstack/echo/v4 v4.15.2); structured logging via log/slog; metrics via Prometheus promauto; Redis-wire client redis/go-redis/v9 v9.19.0; WebSocket via coder/websocket v1.8.14.
  • Control Plane UI — React + Vite + TypeScript (strict mode); React Query via the useApi hook; layered design tokens in packages/ui-shared/src/styles/ (global.css raw → light.css / dark.css semantic, flipped by data-theme); i18n with react-i18next (en / zh / es under packages/control-plane-ui/public/locales/ and src/i18n/locales/); tests via Vitest.
  • Database — PostgreSQL 16. Prisma is the dev-time source of truth (tools/db-migrate/); runtime queries use hand-written SQL + pgx.
  • Cache — Valkey 8 (Redis-wire-compatible, BSD-licensed valkey/valkey-bundle:8-trixie image). Pure cache only — no pub/sub anywhere.
  • MQ — NATS JetStream behind the packages/shared/transport/mq/ interface.
  • Monorepo — npm workspaces (packages/control-plane-ui, packages/agent/ui/frontend, tools/db-migrate) + go.work for Go.

Go workspace — what every build context must carry

Every Go module under packages/ references its sibling workspace packages by require github.com/AlphaBitCore/nexus-gateway/packages/<sibling> v0.0.0-<timestamp>-<commit>. Those pseudo-version requires are only there to make each module syntactically valid on its own — real resolution comes from go.work at the repo root.

This has one consequence: if go.work is missing from the build context, Go falls back to the literal pseudo-version in require and tries to fetch the module from GitHub instead of using the local source tree. The build "succeeds" against an old remote snapshot, masking local changes.

Rules for every build environment:

  • Fresh clonegit clone already includes the committed go.work and go.work.sum. Run go build from inside the repo.
  • Docker — copy go.work + go.work.sum and every packages/<module> directory the service transitively depends on, not just the service's own folder. Minimum viable layout:
    WORKDIR /build
    COPY go.work go.work.sum ./
    COPY packages/shared       packages/shared
    COPY packages/<svc>        packages/<svc>
    WORKDIR /build/packages/<svc>
    RUN go build -o /out/<svc> ./cmd/<svc>/
  • CI — use full actions/checkout (default fetch-depth, no sparse-checkout).
  • Sanity probeGOWORK=off go build ./cmd/<svc>/ from inside a workspace package should refuse to build or pull a remote snapshot.

If a contributor reports "Go keeps downloading our own modules from GitHub", the answer is always: their build context is missing go.work (or they have GOWORK=off set).


Common commands

Command Purpose
./scripts/dev-start.sh One-shot bootstrap (Docker + DB + seed + UI)
npm run dev:control-plane-ui Start the UI dev server only
make build-all Build the Go services + UI. Go binaries land in dist/bin/<service>/<binary>.
make test-all Run go test -race -count=1 for every Go module + UI Vitest
make clean Remove dist/bin/ and packages/control-plane-ui/dist/. Platform agent packages under dist/{macos,linux,windows}/ are preserved — clean those via the per-platform targets (agent-clean-macos, agent-clean-windows).
npm run check:all Run every pre-commit lint (i18n parity, design tokens, terminology, migration timestamps, useApi keys, sidebar icons, …). CI runs the same set.
npm run db:migrate Create a new Prisma migration in tools/db-migrate/

To build, sign, notarize, or package the macOS Agent (.app / .pkg), always invoke the build-agent Claude Code skill — not the raw wails / codesign / notarytool commands. See CLAUDE.md → "macOS Agent builds MUST go through Skill('build-agent')" binding rule for why.


Authoritative documents

  1. CLAUDE.md — binding charter. Plan + Todo gate, English-only artifacts, IAM impact review, macOS NE fail-open, pre-edit reading, completion-time self-audit, real-implementation-only, development-phase greenfield policy.
  2. CONTRIBUTING.md — workflow summary, pre-commit checks, high-blast-radius surfaces, review pointers.

Acknowledgments

  • Project Maintainer — the original idea behind Nexus Gateway came from him, and he stayed hands-on throughout: code, tests, design reviews, architectural decisions.
  • The wider team — engineers, code reviewers, QA, design folks, and the people running prod. The architecture decisions, design reviews, code-review catches, and prod incidents that shaped this codebase all came from team collaboration.
  • Claude Code — Anthropic's CLI assistant did the lion's share of the implementation work, side-by-side with the human maintainers.

AI is already here. Keep learning, keep adapting.