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Process 3D scan data with CloudCompare through text commands. Clean point clouds, collections of measured 3D points, extract ground surfaces, align scans, calculate distances, and convert or export point clouds and surface meshes in supported formats.
Compare two GEO audits, which assess a site's readiness for AI search visibility, and produce a monthly client report. Summarize score changes, crawler access, completed actions, newly discovered issues, and priorities for the following month.
Designing side-by-side comparison tools (plan-compare, product-compare, alternative-compare) that help users decide rather than just listing features. Axis selection, default-comparison logic, recommendation discipline. Honest about feature-list-dump (every feature in a row, no decision support), hidden-recommendation (biased comparison pretending to be neutral), and honest-comparison-with-guidance (genuine comparison plus opinionated recommendation) patterns. Triggers on comparison tool, plan compare, product compare, alternative compare, vs page, decision support tool. Also triggers when conversion through comparison stages is poor, when users are abandoning at the comparison step, or when a comparison tool is being scoped for the first time.
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Find AI models for a specific task using official Hugging Face benchmark leaderboards. Compare scores, model sizes, and licenses, with memory-based estimates of device suitability and flags for models requiring quantization or API access.
Use when user asks to compare masters, compare schools, compare perspectives, 对比, 各宗怎么看, 不同宗派, 禅净之争, 性相之辩, 空有之争, or wants multiple masters to answer the same question. Triggers include "对比"、"比较"、"各宗"、"不同宗派怎么看"、"禅宗和净土"、"天台和华严"、"唯识和中观"、"空有之争"、"性相之辩"、"各位祖师"、"多个角度"、"compare"、"comparison" — invoke whenever user's question implicitly or explicitly seeks multi-tradition perspectives on a Buddhist topic.
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Compares two Prof datasets (GPU vs NPU / NPU vs NPU) by auto-installing and calling msprof-analyze compare, then parses the result xlsx into HTML report and Chinese xlsx. Invoke when user provides two prof dirs to compare, or has a compare result xlsx to analyze/translate.
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Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences, cohorts, or groups — for example, "how do mobile users compare to desktop users on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison," "audience comparison," or "cohort comparison."
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Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences or visitor groups — for example, "how do mobile visitors compare to desktop on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison" or "audience comparison."
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Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences or visitor groups — for example, "how do mobile visitors compare to desktop on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison" or "audience comparison."
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Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences, cohorts, or groups — for example, "how do mobile users compare to desktop users on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison," "audience comparison," or "cohort comparison."
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Compare historical consumer prices, interest rates, and government bond yields from stored official reports. Keep source dates, index bases, reporting frequency, yield definitions, and missing observations visible when examining trends across countries.
Evaluate BMad skills using your agent's configured runner. Compare results with the model alone or another version, grade outputs against criteria, and test whether descriptions trigger correctly, preserving transcripts and evidence for each run.
Simulate concentration changes over time from biochemical models in SBML or Antimony, and compare fixed parameter conditions. Checks model units and exports CSV results plus COMBINE archives containing models and experiment settings, then replays them to compare results.
Research products against a budget and required features, then compare prices, specifications, and review findings in a table. Get one recommendation with its tradeoff, plus a price history check for deals when available.
Retrieve current Azure retail prices and estimate monthly or annual costs by service, region, and configuration. Compare payment options and calculate Copilot Studio credit usage and estimated costs from expected agent activity.
Compare job offers using salary, equity, benefits, and working conditions. Build side-by-side tables for first-year and ongoing compensation, then score career growth, team culture, and other factors according to personal priorities.
Examine writing for familiar AI patterns, statistical features, Pangram detection scores, and hidden character signatures. Compare drafts against known human writing to interpret the evidence, with explanations and limitations rather than a definitive authorship claim.
Save a page's SEO settings and compare them with later versions to detect changes after updates or deployments. Review differences in titles, headings, indexing controls, structured data, and available performance metrics, with severity levels and stored comparison history.
Compare API performance across versions — regression detection and root cause analysis. Use when asked "did performance regress", "compare API latency across versions", or "why is this slower".
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Compare Google Search Console performance between two time periods to identify trends and changes. Supports month-over-month (MoM), year-over-year (YoY), or custom date ranges. Use when user says "GSC compare", "period comparison", "month over month", "year over year", "compare performance", "MoM", or "YoY".
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Compare standardized metrics across multiple ego-benchmark-harness runs by recalculating them from tasks.jsonl and session JSONL, never from HTML reports. Covers overall aggregates (success rate/average score), Odysseys per-rubric pass rates, duration distributions (avg/p50/p90/max), turns/tools/cost, error and exception counts, per-task success matrices, helper distributions, and the share of DOM operations. Use whenever users ask to compare data or metrics across runs, calculate aggregate/Odysseys/duration/turn/error/helper metrics, inspect differences among runs, or compare multiple rwb/real-world-bench runs. Use pi-session-analyzer instead for deep forensic analysis of why an individual task was slow or failed.
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Map the impact of a proposed change using real dependencies and project documentation. Identify affected code, data, interfaces, tests, and release steps, then compare the implemented changes with the plan to expose gaps and unverified risks.
Browse Itô baskets, collections of prediction-market items, and organize market data with sources and timestamps. Compare baskets with selected research or watchlists, prepare market briefs, or draft planning worksheets for manual review without investment advice or trading.
Look up stock and cryptocurrency prices, find ticker symbols by company name, and compare several stocks. Uses Yahoo Finance data to return daily price history, trading volume, and performance statistics in a structured JSON format.