Results for “pr”

Build, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".

Run a Codex prompt repeatedly on a fixed interval. Use for "/loop", "run this every N minutes/hours", "poll X every 5 minutes", "repeat this Codex prompt", or any recurring interval-based Codex job. This is the interval-repeat companion to the separate `schedule` skill (cron / specific-time). For a durable, always-on alternative that survives reboots and terminal exits, prefer Codex app Automations; this local CLI is a terminal fallback that only fires while its daemon process is running.

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

Manage Azure AI Foundry projects with .NET SDK: create and run agents, manage connections, datasets, deployments, evaluations, and indexes.

Creates Azure OpenAI model deployments with intelligent intent-based routing, supporting quick presets, full customization, and capacity discovery across regions and projects.

Accelerate pandas workflows with GPU DataFrames using cuDF and dask-cuDF for ETL, joins, groupby, and large-scale data processing.

Generates comprehensive test strategies, task breakdowns, and quality assurance documentation for GitHub projects using ISTQB and ISO 25010 frameworks.

Build a persistent, compounding knowledge base that combines a wiki, knowledge graph, and raw source storage for structured retrieval with provenance.

Generates a complete Kotlin MCP server project with Gradle structure, dependencies, and implementation using the official kotlin-sdk library.

Scan Model Context Protocol servers and tool metadata for poisoning, SSRF, and unauthenticated exposure.

Apply foundational design principles—affordances, signifiers, constraints, mappings, and feedback—to evaluate and improve product usability, bridging the gulfs of execution and evaluation.

Run ML workloads on Modal's serverless GPU cloud platform with auto-scaling, pay-per-second pricing, and Python-native infrastructure.

Guide a visible, verified code walkthrough in Neovim with Terminal Control and Navi, optionally recording the presentation with OBS or retaining terminal evidence.

Covers AI, machine learning, LLMs, prompt engineering, and blockchain development with code examples and best practices for building AI applications and smart contracts.

Generates images via OpenAI, Google, DashScope, and Replicate APIs, supporting text prompts, reference images, aspect ratios, and quality presets.

Calculates polygenic risk scores from 23andMe or AncestryDNA genotype files using PGS Catalog scoring files, then estimates population percentiles and risk categories.

Converts code repositories and document directories into semantically-chunked text files optimized for NotebookLM ingestion, with support for config files and incremental processing.

Generates structured VGL JSON for Bria FIBO models, giving deterministic control over objects, lighting, camera, composition, and style instead of natural language prompts.

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

基于 Modular RAG MCP Server 项目生成定制化简历项目经历。结合项目技术亮点与用户业务场景，按简历编写原则输出高质量项目描述（中英文）。Use when user says '写简历', 'resume', '简历', 'write resume', '项目经历', 'project experience', '简历项目', or asks to generate resume content based on this project.

基于 Modular RAG MCP Server 项目生成定制化简历项目经历。结合项目技术亮点与用户业务场景，按简历编写原则输出高质量项目描述（中英文）。Use when user says '写简历', 'resume', '简历', 'write resume', '项目经历', 'project experience', '简历项目', or asks to generate resume content based on this project.

Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.

Use this skill for performance, reliability, observability, SLO risk, production diagnostics. Trigger when the task involves agent profile work related to Performance SRE Agent, implementation, audits, debugging, strategy, or validation.

Design a fact-checking protocol for AI-generated text, extending SIFT with AI-specific adaptations for hallucination detection. Use when students need to verify AI claims and citations.

Expose the processkit MCP tool surface through a single stdio server. Use for harnesses that eagerly start every configured MCP server, such as Codex, while keeping per-skill MCP servers available.

Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

Train machine learning models end-to-end, covering data loading, preprocessing, architecture selection, training loops, validation, and checkpointing. Use when the user requests model training or provides relevant inputs for this workflow.

Applies Han's shared Human-Readable Output Standard to a target you already have — a file on disk, text pasted into the prompt, or a draft already produced in the conversation — by dispatching the readability-editor to rewrite its prose so the main point comes first, headings are descriptive, each paragraph carries one idea, and sentences stay short and active, while preserving every fact. Use when you want to make a document or draft readable, edit or polish prose for readability, clean up writing, tighten wording, or re-apply the readability standard to something already written. Rewrites prose only, leaving code, diagrams, and citation identifiers unchanged. Does not write new feature or system documentation — use project-documentation. Does not restructure code or review it — use refactor to restructure code and code-review to audit it. Does not judge the underlying work or raise findings; it only rewrites the writing.

Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).

Implement Google's BeyondCorp zero trust access model to eliminate implicit trust from the network perimeter, enforce identity-aware access controls using IAP, Access Context Manager, and Chrome Enterprise Premium for VPN-less secure application access.

Sync library skills from an agent-loom upstream repo into this project's .agents/skills while preserving project-local and forked skills. Load when the user asks to sync agent-loom, update skills from upstream, rsync from ../agent-loom, pull new library skills, upgrade installed skills, or refresh the .agents folder without losing custom project skills. Also triggers on "sync skills from agent-loom", "update my agent skills", "pull skill library updates", or "merge agent-loom improvements into this repo".

Write, review, and migrate code using NVIDIA DALI's imperative dynamic-mode API for efficient data loading and preprocessing.

Scans agent skills for security issues including prompt injection, malicious scripts, excessive permissions, secret exposure, and supply chain risks.

Automate Payhip e-commerce operations like sales management, product updates, and customer management through Composio's Payhip toolkit via Rube MCP.

Converts abstract edge concepts into concrete strategy draft variants with configurable risk profiles and optional exportable ticket YAMLs for downstream validation.