Results for “runs”

Runs comprehensive SEO audits and analysis for any website, covering technical SEO, content quality, schema markup, sitemaps, images, and GEO, with industry-specific detection and actionable recommendations.

Runs comprehensive SEO audits and analysis for websites, covering technical SEO, content quality, schema markup, Core Web Vitals, local SEO, and AI search optimization using browser automation tools.

Runs a structured 6-phase security audit covering attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, plus incident-response and monitoring playbooks.

Runs a three-layer verification pipeline on AI-generated output: extracts verifiable claims, finds supporting or contradicting sources via web search, and produces a structured verification report with source links for human review.

Executes Atomic Red Team tests mapped to MITRE ATT&CK techniques, performs coverage gap analysis, and runs detection validation loops to measure blue team visibility.

Runs a full retrospective and dev cycle analysis, chaining /recall and /new-features to reconstruct what went wrong, extract lessons learned, identify rework patterns, and synthesize feature ideas from the findings.

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.

Runs a post-launch review of a shipped PRD against its success metrics, interviewing the user on metric movement, assumptions, and decisions, then publishing an outcome-review page to Confluence and updating linked artifacts.

Runs an evidence-first, read-only workflow over large codebases via an external JSONL REPL server, retrieving only minimal file slices and greps to produce cited architecture and audit reports.

Prediction market arbitrage & alpha scout. Searches Polymarket and Kalshi for the same event, runs cross-platform arb math (including fees), and ranks opportunities by profitability. Use when asked to "find arb", "scout markets", "find edge", or scan a specific topic across prediction markets.

Lightweight ContentShake AI self-check the /draft stage can call before saving. Returns just SEO + Quality scores (no full optimization) so the writer knows whether the draft is in winning territory before /quality-check runs. Fails soft when SEMRUSH_API_KEY is unset.

React component testing with React Testing Library, Vitest/Jest, MSW for network mocking, accessibility assertions with axe, and the decision boundary between component tests and Playwright/Cypress end-to-end runs. Use when writing or fixing tests for React components, hooks, or pages.

Autonomously runs iterative experiment loops to optimize code against a measurable metric. Use when the user wants to improve execution time, memory usage, test pass rate, or any numeric performance goal across repeated experiments — NOT for one-shot bug fixes or simple code review.

Critically audit agent skills and remove content that is outdated, disproven, model-specific, or based on poorly cited sources. Load when improve-skills runs its per-skill cycle, when the user asks to prune skills, remove outdated techniques, check if skills are still valid, verify citations in skills, audit skill sources, or update skills for a new model release. Also triggers on "are these skills still valid", "check for obsolete techniques", "verify skill citations", or "update skills for GPT-5/Claude 4/Gemini 2". Runs before split-skill and compress-skill — removing bad content first means the remaining content is worth preserving.

Runs a side-by-side walk-forward backtest of a Bull Put Spread strategy with and without a FearScore entry signal, comparing performance metrics over ~8 years of daily data.

Generates a complete mobile test suite for Flutter, React Native, iOS, or Android apps, covering unit, widget, integration, snapshot, accessibility, and platform-specific tests, then runs them with a self-healing loop.

Runs a full website SEO audit by crawling up to 500 pages, detecting business type, delegating to specialist subagents, and producing a prioritized action plan with a health score.

Losslessly compress PNG and SVG assets in place and generate .webp siblings for every raster image. Use when the user asks to "compress assets", "optimize images", "shrink the assets folder", or "convert to webp". Runs a deterministic pipeline via oxipng + svgo + cwebp + ImageMagick.

Daily inbound freelance-job discovery across the markets and platforms the brand chose — scrapes job posts via Claude in Chrome (Freelancer.com API where available), scores each for service fit, deduplicates, and drops matches into a Notion opportunities DB. Runs daily on cron schedule.

Runs a closed-loop SEO growth workflow using Search Console data, keyword demand analysis, SERP Authority Mark checks, and the available publishing path, adapting to CMS/API, local repo, hybrid, and advisory-only environments.

Runs a headless-Chromium sweep at phone/tablet widths to catch off-screen overflow, tiny touch targets, clipped text, and oversized modals, then reports each offender with a screenshot and a concrete fix.

Runs a full marketing and sales operation for solo founders, covering customer research, content creation, SEO, paid ads, email sequences, CRO, pricing, retention, analytics, and automation with stage-based playbooks.

Consolidates project memory across harness and .memory/ with theme clustering, practical-expiry prune, ground-truth verify, and an adversarial second pass. Use when the user runs /memory:consolidate, asks to tidy/dedupe/prune memory, or reports redundant or stale memories. Also covers active writing during work.

Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says "DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning.

Use when starting a new research project, exploring a research idea, deciding whether a question is viable, or before touching code or data for a new paper. Runs a research-focused brainstorm that clarifies research question, identification strategy, data feasibility, and contribution before any implementation.

Runs a deep cross-layer consistency audit across a codebase, tracing features from UI to database to find broken wiring, missing handlers, model mismatches, and security gaps, then auto-fixes critical and warning issues.

Personal CRM built on monday.com. Tracks contacts, last interactions, next meetings, and topics. Runs daily to update from Calendar + email. Delivers pre-meeting briefings as part of morning-briefing. Use when: someone asks about a contact, before a meeting, or during daily CRM sync.

Runs Python code in the cloud with Modal — serverless containers, on-demand GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that need GPU acceleration or dynamic scaling. Part of the AlterLab Academic Skills suite.

Runs a comprehensive mobile QA audit covering permissions, deep links, push notifications, offline mode, background/foreground transitions, memory leaks, network conditions, accessibility, and platform edge cases for Flutter, React Native, and native iOS/Android apps.

Adopt Swift 6.2's Approachable Concurrency model, which runs code single-threaded by default and uses explicit @concurrent for background offloading, isolated conformances, and MainActor default inference to eliminate data-race errors.

Conversion Rate Optimization auditing for landing pages, signup flows, checkout funnels, forms, and CTAs. Identifies friction points, runs heuristic evaluations, produces prioritized recommendations using ICE/PIE frameworks. Use when the user asks about conversion optimization, funnel analysis, landing page audits, form optimization, CTA testing, or checkout improvement.

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

Proofread and verify academic papers in LaTeX. Runs 19 sequential checks covering titles, consistency, citations, formatting, theoretical tension in motivation, concise results reporting, cross-section repetition, em-dash usage, and auxiliary-text-to-footnote conversion. Trigger when user says "check paper" / "proofread" / "paper-checker" / "校对" / "核查论文".

Generates and runs load tests for API endpoints using k6, Locust, or Artillery. Detects the API framework, creates realistic user behavior flows, executes ramp-up, sustained, spike, and stress profiles, and produces a bottleneck analysis with optimization recommendations.