Results for “8k4-protocol”

Drafts SEC Form 8-K current reports with item-accurate narratives, exhibit indexing, and EDGAR-ready formatting. Use when a public company must disclose a reportable event (material agreement, acquisition, personnel change, Reg FD disclosure) or file a current report within four business days. Trigger on "Form 8-K", "current report", "8-K filing", "EDGAR", "Item 1.01", "Item 2.01", "Item 5.02", "Reg FD".

How MaksPM hands off work to agents using sessions_spawn for continuous pipeline flow, with file-reference pattern for preserving full project specs. Updated 2026-03-21 with 9-phase pipeline and Forge architecture phase.

Creates detailed, bite-sized implementation plans from specs or requirements, with exact file paths, code, and TDD steps.

Provides a general standard operating procedure for handling requests related to news reports about Chinese leadership visits, including title generation and step-by-step execution guidance.

阶段④ 执行。主 agent 跟踪进度 + 并行派生子 agent 实现模块，含代码门禁与调试档位。

Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says "rebuttal", "reply to reviewers", "ICML rebuttal", "OpenReview response", or wants to answer external reviews safely.

封装阶段3的Copy Spec为可批量执行的提示词包，生成JSONL请求并调用APIMart API出图。

Guides implementation of GDPR Article 42-43 data protection certification mechanisms including accredited certification bodies, criteria development, and periodic review. Activate when pursuing privacy certifications, evaluating certification bodies, or developing certification criteria. Keywords: certification, Article 42, Article 43, accreditation, seal, privacy mark.

Parses external reviews, enforces coverage and grounding, and drafts a text-only rebuttal under venue limits, managing follow-up rounds.

Guides a structured planning pipeline for coding tasks, from scoping and research to plan creation, review, and handoff.

Authorized reverse engineering of custom binary protocols, Protobuf/gRPC, WebSocket frames, and PCAP-driven protocol recovery with structured workflow and tooling.

Provides production-grade Kubernetes YAML patterns and kubectl debugging commands for deploying, managing, and debugging workloads reliably.

Provides Ethereum token and protocol standards including ERC-20, ERC-721, ERC-1155, ERC-4337, ERC-8004 agent identity, EIP-7702, EIP-3009 gasless transfers, and x402 HTTP payment protocol.

Generates an operations runbook from deployment configs, CI/CD pipelines, and monitoring setup, with copy-pasteable procedures for deployment, rollback, scaling, database maintenance, incident response, and troubleshooting.

Chunks a book into canonical retrieval units with heading-aware structure splitting, recursive token targets, and contextual prefixes for downstream RAG ingestion.

Implements a simplified version of the Signal Protocol's Double Ratchet algorithm using X25519, HKDF, and AES-256-GCM for end-to-end encrypted messaging.

Integrate Hardware Security Modules (HSMs) using the PKCS#11 interface for cryptographic key management, signing operations, and secure key storage with python-pkcs11, AWS CloudHSM, and YubiHSM2.

Guides a structured planning pipeline for coding tasks, including scope detection, research, plan creation, and review.

GPT-4V(ision) System Card

Captures operational workflows, release procedures, incident patterns, or support processes as repeatable runbooks.

Guides the creation and review of data processing agreements under GDPR Article 28(3), covering all eight mandatory clauses. References the 2021 Standard Contractual Clauses and provides a compliance checklist for processor contracts. Activate when onboarding processors, reviewing DPAs, or auditing processor compliance. Keywords: DPA, data processing agreement, Article 28, processor, mandatory clauses, standard contractual clauses.

Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.

Guides the creation, editing, and verification of agent skills using a test-driven development approach, with structured documentation and quality gates.

Runs a structured bug-fix pipeline: scouts evidence, diagnoses root cause, applies minimal fixes, and reviews before committing.

Delegates a bounded repository task to an allowlisted external coding CLI through a guarded runner, with provider selection, timeout handling, and independent local review.

Register AI agents on Ethereum mainnet with a verifiable on-chain identity using ERC-8004, including bridging ETH, IPFS upload, and on-chain registration.

GPU-safe parallel processing patterns for KINTSUGI to prevent OOM crashes and ensure Jupyter-compatible progress output

Drafts stipulated ESI protocols for federal e-discovery. Produces court-ready agreements governing preservation, collection, processing, review, and production of electronically stored information under FRCP Rules 26, 34, 37 and Sedona Principles. Trigger when formalizing ESI procedures between parties during the discovery phase.

Provides patterns for hydration safety, performance, route rules, lazy loading, and SSR-safe data fetching in Nuxt 4 apps.

Provides a structured protocol for receiving and evaluating code review feedback, emphasizing technical verification over performative agreement.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

Humanization Pipeline Orchestrator v3.1 - Multi-pass 4-layer transformation pipeline Orchestrates G5 (Auditor), G6 (Humanizer), F5 (Verifier) in sequential passes Enforces checkpoints between every pass with mandatory AskUserQuestion Supports conservative (L1-2), balanced (L1-3), balanced-fast (L1-3 merged), aggressive (L1-4) modes Rich Checkpoint v2.0: section-level scores, selective humanization, target auto-stop G5+F5 parallel execution, section-selective humanization Triggers: humanize, humanize my draft, humanize manuscript, make natural, remove AI patterns Korean triggers: 휴먼화, 자연스럽게, AI 패턴 제거

Use when running QA Lab channel message flow evidence.

Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API.

Manage n8n workflows, executions and credentials via REST API