Results for “compare”

Monthly delta tracking and progress reporting for GEO clients. Compares two GEO audits (baseline vs. current), calculates score improvements across all categories, tracks action item completion, and generates a "here's your progress" client report. Use when user says "compare", "delta", "monthly report", "progress", "confronta", "progressi", "report mensile", or when running a monthly client check-in.

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Compare your data to a partner's data in the marketplace. Given a dataset you already own with person/edge data, this skill walks you through picking a partner data source to match against, choosing which identifier types to match on, optionally selecting which enrichment attributes to attach, and then submits the report — returning overlap, match counts, and demographic coverage. Use when: "how does my data compare to your marketplace", "compare my data to [partner]", "how much overlap do I have with [supplier]", "run a match report", "match my customers against 3P data", "see what enrichment is available for my dataset", or any open-ended question about marketplace overlap. (narrative-identity)

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Use when the user wants to send the same prompt to several LLMs and compare the answers - sequentially (stopwatch, clean per-lane timing) or in parallel (true race), with optional repetitions per model, judged by the starting model across quality, correctness, completeness, instruction fidelity and latency (time is only one dimension). Triggers on /compare-race, 'model race', 'vergleiche modelle', 'gleicher prompt an mehrere modelle'.

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Cross-model benchmark for gstack skills. Runs the same prompt through Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens, cost, and optionally quality via LLM judge. Answers "which model is actually best for this skill?" with data instead of vibes. Separate from /benchmark, which measures web page performance. Use when: "benchmark models", "compare models", "which model is best for X", "cross-model comparison", "model shootout". (gstack) Voice triggers (speech-to-text aliases): "compare models", "model shootout", "which model is best".

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Build temporary OpenClaw terminal interfaces with fixed sample data and compare two to six interactive designs side by side in tmux, a terminal pane manager, using the actual rendering components without running the full application.

• Comparing onboarding screen designs
• Trying chat or selector layouts
• Comparing an existing screen with alternatives

Test an idea before committing to full development by building a small, disposable prototype. Compare approaches under equal conditions, try a failure case, and report feasibility with commands, results, or measurements supporting the verdict.

• Testing whether an idea is technically feasible
• Comparing two approaches under the same conditions
• Checking an edge case before full development

Investigate shipped applications, binaries, packages, and firmware with REA to explain features, compare versions, or guide reconstruction. Use decompiled code and runtime observations where needed, keeping observed facts, inferred behavior, and unresolved questions clearly separated.

• Explaining features in a shipped application
• Comparing behavior across application versions
• Inspecting binaries and packaged resources

Review a codebase for structural problems that make understanding and testing difficult. Compare refactoring candidates in an HTML report with before-and-after diagrams, then explore the chosen option through questions about constraints, design, and tests.

• Review architecture in frequently changed code
• Compare refactoring options with before-and-after diagrams
• Explore module designs that are easier to test

Plan manufacturing jobs around available machines, operators, materials, and delivery dates. Use bottleneck analysis, changeover planning, and workload balancing to compare production sequences and revise schedules when breakdowns, shortages, or absences disrupt the plan.

• Sequence jobs competing for limited equipment
• Revise production schedules after equipment breakdowns
• Compare batch sizes and changeover costs

Research current facts, compare options, or investigate people and companies using public sources and supplied context. This skill selects an appropriate research workflow and separates evidence, inference, and recommendations, including dates where freshness matters.

• Check current facts against existing documents
• Compare options before making a decision
• Research potential contacts and companies

Measure web page speed, API response times, and build or test duration. Save baseline measurements as JSON tracked in Git, then compare results before and after changes to identify performance regressions and assess launch targets.

• Comparing performance before and after a code change
• Investigating reports that a page feels slow
• Checking performance targets before launch

Check deployed URLs after releases for page and API failures, broken assets, streaming connection issues, and slower performance. Run a single check, monitor over a set period, or compare staging and production with baseline reports.

• Checking production or staging after deployment
• Verifying fixes after merges or dependency upgrades
• Monitoring a site during its launch window

Find language models on Hugging Face Hub and run them locally with llama.cpp. The skill helps compare GGUF model files, choose compressed versions that fit available memory, and prepare commands for a local chat server or command-line session.

• Find a model that fits local RAM or GPU memory
• Compare available GGUF files and sizes
• Prepare a local chat server command

Turn researched property and rental details into browsable cards in Hermes desktop conversations. Each card can show photos, prices, features, source links, and questions to check, keeping shortlisted properties easy to compare during follow-up discussions.

• Compare shortlisted rental properties
• Organize property photos, prices, and features
• Review questions to check before a viewing

Explore a screen design through two or three interactive HTML mockups. Compare distinct layouts, information density, and visual approaches, with notes on each option’s strengths and trade-offs to help choose a direction before implementation.

• Comparing screen layouts before implementation
• Exploring compact and spacious design options
• Testing filters or panel interactions in a mockup

Audit a developer product by trying its documentation and setup flow, measuring onboarding time, capturing errors, and reviewing command-line help. Produce an evidence-backed scorecard and compare results with earlier planning scores when available.

• Try a developer product's documentation and setup flow
• Measure onboarding time
• Review error messages and command-line help

Investigate slow PostgreSQL queries in Paperclip, reproduce their cost locally, and implement measured fixes. Compare performance and returned results, add regression coverage, and carry pull requests through review and automated checks.

• Investigate slow requests with a suspected database cause
• Reduce the cost of frequently repeated queries
• Compare query speed and results before and after a fix

Produces detailed HTML or Markdown reports on pull requests, branches, or large code contributions. It explains how the system works, ranks concrete findings, compares designs when needed, and recommends whether and how to merge the changes.

• Reviewing a large pull request in depth
• Explaining a contribution’s design and behavior
• Comparing a design with similar systems

Prepare and submit requests to add agents in Paperclip. Check hiring permissions, compare existing configurations, and define the role, instructions, reporting line, and runtime settings, then handle approval and follow-up for linked tasks.

• Requesting a new agent for a specific role
• Matching a new agent to existing team settings
• Drafting role instructions and runtime settings

Compare changes across Git worktrees, branches, and pull requests through a facilitated discussion between agents. Produce one consolidation plan covering the target worktree, merge order, conflicts, and decisions that need human input.

• Planning how to combine work from multiple branches
• Comparing overlapping changes and competing implementations
• Reviewing recent worktrees together

Train and evaluate models that estimate human poses from WiFi signals. Compare results against a model that always predicts the average pose, check for data leakage, and report measured improvements with clear evaluation conditions.

• Train a pose model using camera labels
• Evaluate pose estimation without a camera at inference
• Compare accuracy against an average-pose baseline

Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.

• Compare performance before and after v3 optimization
• Evaluate vector search speed and memory use
• Track performance regressions over time

Measure Storybook startup from launching the process to displaying the first story. Separate server readiness from browser rendering, summarize repeated runs, and compare versions or feature flags to investigate slower startup.

• Measure startup through the first story render
• Compare Storybook versions or feature flags
• Summarize repeated startup measurements

Analyze Excel and CSV files to summarize statistics, filter records, compare groups, and join data across sheets or files. Export results as CSV, JSON, or Markdown tables for further work or sharing.

• Compare monthly sales and top-selling products
• Combine order records with customer data
• Check missing values and statistical summaries