Results for “ai-safety”

Train AI models to be harmless through self-critique and AI feedback using a set of constitutional principles, without requiring human labels for harmful outputs.

Performs a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.

Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.

Formats git commits using Sentry conventions with conventional commit types, issue references, and AI attribution, while enforcing branch safety.

Route AI agent engineering prompts to architecture, orchestration, evaluation, safety, debugging, context, prompt, MCP, persona, local AI, and Compound Engineering skills. Use when prompts mention agents, agent harnesses, agentic workflows, orchestration, evals, context management, MCP servers, or compound engineering.

Enforces production-grade Python and AI engineering standards for FastAPI, LangChain/LangGraph, RAG pipelines, and LLM integrations, covering type safety, error handling, testing, and security.

Safety guardrails for autonomous agents. Intercepts destructive actions and vets skills, requires structured approval before irreversible operations, with CLI-backed cryptographic audit trails and policy enforcement.

Sovereign-grade safety OS for AI coding agents. 63 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.

Perform a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.

Orchestrates Gemini 3 Flash to audit Linux Kernel patches for memory safety, detect cost drifts in Terraform plans, and generate hardened Kubernetes security contexts.

Manages Ray clusters, jobs, Serve deployments, and distributed workloads via the Dashboard API and CLI, with discovery-first checks and safety guardrails.

Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?"

Analyze read-only dividend metrics for stocks via AIsa API. Provides yield, payout ratio, growth CAGR, safety score, income rating, and Dividend Aristocrat/King status without placing trades, making purchases, or managing brokerage accounts. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.

Analyze read-only dividend metrics for stocks via AIsa API. Provides yield, payout ratio, growth CAGR, safety score, income rating, and Dividend Aristocrat/King status without placing trades, making purchases, or managing brokerage accounts. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.

Use to audit a customer-facing support bot or AI agent for harm rather than for volume — manipulation and prompt-injection attempts, customers stranded without a human, fabricated answers, and unsafe commitments or disclosures. Trigger for "are people trying to jailbreak our bot", "show me attempts to manipulate the assistant", "is our bot giving wrong answers", "customers stuck with the bot and never got a human", or reviewing an AI agent before or after launch.

Generate images with Google Nano Banana 2 (Gemini-family flash-tier text-to-image) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Nano Banana 2's strengths (rapid iteration, in-image typography rendering, predictable framing, optional web-grounded context), the resolution-tier pricing, the safety-tolerance dial, and when to route to Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream instead. Calls `runcomfy run google/nano-banana-2/text-to-image` through the local RunComfy CLI. Triggers on "nano banana", "nano-banana-2", "nano banana 2", "google image gen", "gemini image", or any explicit ask to generate with this model.