Results for “pr-gate”

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Use for all ClawSweeper work: MarketingClaw issue/PR sweep reports, commit-review reports, repair jobs, cloud fix PRs, @clawsweeper maintainer mention commands, trusted ClawSweeper-reviewed autofix/automerge, GitHub Actions monitoring, permissions, gates, and manual backfills.

Expert knowledge for Azure Bastion development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring Bastion for AKS private clusters, VM scale sets, Entra ID auth, hub/spoke VNets, or native SSH/RDP clients, and other Azure Bastion related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual Machines (use azure-virtual-machines), Azure VPN Gateway (use azure-vpn-gateway), Azure Firewall (use azure-firewall).

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Operates Laravel applications in production, covering Horizon, queues, scheduler, Octane, Redis, Supervisor, PHP-FPM, cache, and deployment with safety gates for destructive commands.

Expert knowledge for Azure Virtual WAN development including troubleshooting, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Virtual WAN hubs, P2S VPN, hub routing/BGP, NVAs/SD‑WAN, or ExpressRoute/Private Link integration, and other Azure Virtual WAN related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure VPN Gateway (use azure-vpn-gateway), Azure ExpressRoute (use azure-expressroute), Azure Traffic Manager (use azure-traffic-manager).

Reviews all pipeline artifacts from a virtual software team and produces quality, compliance, and sign-off reports with an advisory release verdict.

Detect and prevent privilege escalation in Kubernetes pods by monitoring security contexts, capabilities, and syscall patterns with Falco and OPA policies.

Expert knowledge for Azure Front Door development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring Front Door routing/caching, rules engine, TLS/origin auth, CDN video delivery, or POP limits, and other Azure Front Door related development tasks. Not for Azure Application Gateway (use azure-application-gateway), Azure Traffic Manager (use azure-traffic-manager), Azure Load Balancer (use azure-load-balancer), Azure Web Application Firewall (use azure-web-application-firewall).

Creates a GitHub pull request with an auto-generated summary, running mandatory pre-commit and code-quality review gates, plus optional deep-review subagents, and posts findings into the PR body.

Validate Azure deployments against functional, security, performance, and operational criteria before production release. Use this skill when users ask for readiness checks, health verification, or production sign-off gates. Covers Well-Architected Framework validation, SLA verification, and release readiness.

Orchestrates the full-site migration preparation cascade — inventory crawl, page-type and module catalog confirmation, archetype prototyping, and asset preparation — with confirmation gates between phases.

Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.

Scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues before deployment. Intercepts deploy commands and blocks until critical items pass.

Full-novel craft + anti-slop pipeline with project mode (ledger, characters, foreshadow, worldbuilding bible), draft→review→revise gates, and stability-trap enforcement at scene/chapter/manuscript scale. Single-scene mode retained. Use for fiction, lore, character docs, dialogue, worldbuilding, or book projects.

Enforces a mandatory pre-commit/pre-PR testing gate: detects the test stack, runs the full suite, fixes failures, creates minimal tests when none exist, and verifies coverage before allowing commits.

Orchestrates a full software development pipeline by sequentially loading and executing seven role-specific skills (BA, TechLead, PM, BE Dev, FE Dev, Tester, QA/QC), with configurable project levels and gate checks.

Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

Operates Redpanda's Agentic Data Plane: manages AI agents, MCP servers, LLM providers, budgets, guardrails, and Cedar access policies via the `rpk ai` CLI and API, including OAuth wiring and spend/transcript insights.

Full test suite improvement composite — audit health, prune dead tests, validate with mutation testing, capture rationale in ADR. Use after a major feature ship, before tightening coverage gates, or when the suite shows bloat, excessive skips, or slow runtime. Chains test-health → test-cleanup → mutation-test → adr-write.

Run metric-driven iterative optimization loops -- define a measurable goal, run parallel experiments, measure each against hard gates or LLM-as-judge scores, keep improvements, and converge on the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation.

Hybrid security auditor for OpenClaw skills, Claude/Codex skills, and app repos. Use when installing a new skill, auditing a repo before use or deploy, reviewing custom scripts, checking for prompt injection, command execution, data exfiltration, dependency risk, secrets exposure, or privilege escalation. Use as the default gatekeeper before installing any third-party skill.

Design and apply QA methodology for software teams: test strategy, regression testing, CI failure triage, test automation, quality gates and metrics, risk-based testing, exploratory testing, test design techniques, AI code quality gates (independent verification, acceptance-criteria testability review for agentic Spec-Driven Development), mutation-guided test hardening and review evidence (surviving mutants, weak assertions, diff-aware mutation testing), agentic eval design (dataset test design, judge-as-system-under-test, flaky-eval discipline), QA career levels (Senior/Staff/Principal), and SDET engineering (test infrastructure, gTAA, CI/CD integration). Do not use for root-cause debugging of production incidents, security implementation or threat modeling, or evaluation framework governance and statistical analysis — route those to systematic-debugging, secure-software-engineering, and agent-evals-and-observability respectively.

SHARK v3.0 — SM Conviction + Liquidation Cascade Hunter. Consolidated from v1.0's 8-cron pipeline into a single scanner. 4-gate entry: SM concentration (30+ traders, 5%+) → top 5 trader alignment → price momentum → funding structure. Score 8+ to enter. DSL manages all exits. No thesis exit. DSL exit managed by plugin runtime via runtime.yaml.

Design and implement CI/CD pipelines and automation — fast checks on every PR, safe releases, and repeatable workflows. Load when setting up GitHub Actions (or similar), adding pre-merge gates, automating releases, or the user asks "add CI", "set up workflows", "automate checks", "CD pipeline". Not for one-off local scripts (use task-specific tooling).

Expert knowledge for Azure Api Center development including best practices, security, configuration, integrations & coding patterns, and deployment. Use when automating API linting/registration, syncing with API gateways, customizing the portal, or managing API inventory, and other Azure Api Center related development tasks. Not for Azure API Management (use azure-api-management), Azure App Service (use azure-app-service), Azure Functions (use azure-functions).

End-to-end game trailer production via the Content Factory trailer_factory pipeline — storyboard → animatic → audio → final cut with inspect-and-fix quality gate. Routes long-running work through Hermes Kanban so it survives pod restarts and exposes a multi-stage status board. Use whenever the user asks for a game trailer, gameplay video, launch teaser, App Store preview video, or any video promoting a game.

Top-layer project orchestration skill for Nick's workflow. Use when a request involves multiple stages, skills, or deliverables and the work needs to stay aligned from idea to scope to design to schema to build to QA to deploy. Coordinates the right sequence, enforces stage gates, prevents drift and overbuilding, tracks status/blockers/next actions, and creates clear handoffs between strategist, design, schema, Supabase, build, QA, and launch work.

Produces durable, structured documentation in codebases with sparse docs — readable by humans and agents alike. Two invocation modes — `survey` proposes a doc plan; `draft` writes one specific doc end-to-end with a factcheck-then-persona review gate. Triggered by phrases like "doxcavate this repo", "doxcavate the X", "doxcavate `runbook-deploy`", "what should be documented?", "document this code", "write a how-it-works for X", or any request to inventory or write project documentation.

Expert knowledge for Azure IoT Edge development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring IoT Edge/EFLOW, DPS/X.509 provisioning, module deployment, gateways, or downstream devices, and other Azure IoT Edge related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT Central (use azure-iot-central), Azure IoT Operations (use azure-iot-operations), Azure Stack Edge (use azure-stack-edge).

Expert knowledge for Azure IoT Central development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing device templates, data export, IoT Edge gateways, REST/CLI automation, or IoT Central–to–IoT Hub migrations, and other Azure IoT Central related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT Edge (use azure-iot-edge), Azure IoT Operations (use azure-iot-operations), Azure Digital Twins (use azure-digital-twins).

Operate and extend barretlee/agent-pulse, the evidence-backed AI industry intelligence system: inspect source catalog and lifecycle, collect and normalize signals, bind evidence, cluster Events, evaluate system health, generate Scout hypotheses, export the privacy-safe public site, and verify release gates. Use when the user asks to run, configure, debug, extend, or explain Agent Pulse, its collectors, Control Room, narratives, Scout, or GitHub Pages output. Triggers on: agent-pulse, Agent Pulse, evidence-backed intelligence, source catalog, signal collection, Event clustering, source audit, Scout opportunity, public export, weekly brief, or AI industry intelligence pipeline.

Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when asked to "auto review", "autoplan", "run all reviews", "review this plan automatically", or "make the decisions for me". Proactively suggest when the user has a plan file and wants to run the full review gauntlet without answering 15-30 intermediate questions. (gstack) Voice triggers (speech-to-text aliases): "auto plan", "automatic review".

Set up pre-commit hooks on a Python project — standard file-hygiene checks plus a security gate (gitleaks secret scanning, Trivy filesystem scan for CVEs/secrets/misconfigs, and Bandit Python SAST). Use this whenever the user wants to add, configure, or fix pre-commit hooks on a Python repo, mentions .pre-commit-config.yaml, wants secret/vulnerability/SAST scanning on commits, or is setting up code-quality guardrails — even if they just say 'add pre-commit hooks' without naming the tools. Especially for uv-based GenAI/LLM backends. Handles the setup gotchas that break first-time installs: the Trivy binary, the required data/html.tpl report template, bandit[toml] + [tool.bandit] config, and the right .gitignore entries.

Drive Animato (github.com/otdnnc/Animato) as an API-key agent loop that turns a rigged .fbx/.gltf model plus a plain-text motion request into a baked animation: upload the model, build the bpy prompt, spend one LLM call with your own key, gate the generated script, run it headless, and verify the animated output. Use when the user wants text-to-animation for a 3D character, an unattended animation pipeline driven by a Gemini or OpenAI-compatible API key, or help operating a local Animato server. Triggers on: animato, text to animation, animate a rigged model, bpy animation script, blender headless keyframe, /api/chat animation, character motion from a prompt, GEMINI_API_KEY animation.