Results for “pe”

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Access blockchain RPC endpoints via Quicknode to read onchain data including balances, token prices, transaction status, gas estimates, and block data across Base, Ethereum, Polygon, Solana, and Unichain. Supports both API key and x402 wallet-based pay-per-request access.

Scrapes posts from a Facebook group given a group URL, sort order, and desired count, returning structured post metadata including post_id, permalink, author, timestamp, body text, media, reactions, comments, and shares.

Guides OLTP database schema design through six stages: domain and access patterns, entities and relationships, keys and constraints, normalization trade-offs, indexing and performance, and operations and evolution. Includes a final review checklist and tips for effective guidance.

Explains MariaDB-specific behavior of DROP USER and RENAME USER, including multiple accounts per statement, IF EXISTS handling, active-connection warnings, and effects on privileges and definers. Use when writing or reviewing account-lifecycle SQL for MariaDB.

Build a quarterly bookings forecast with commit, best-case, and pipe-only tiers, project cohort-level NRR/GRR to surface leaky cohorts, and score per-stage funnel confidence using coefficient-of-variation analysis.

Scrapes tweets from any X (Twitter) URL — search results, user profile, single tweet detail, or list timeline — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and cursor for pagination.

Extracts and analyzes malicious VBA macros, XLM macros, DDE, and remote template injections in Microsoft Office documents using olevba, oledump, and deobfuscation techniques to identify download cradles, payload execution, and persistence mechanisms.

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Supabase administration, RLS policies, migrations, and schema design. Use for database architecture, Row Level Security, performance tuning, auth integration. Activate on "Supabase", "RLS", "migration", "policy", "schema", "auth.uid()". NOT for Supabase Auth UI configuration (use dashboard), edge functions (use cloudflare-worker-dev), or general SQL without Supabase context.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Process and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.

Extracts and analyzes firmware images using binwalk to identify embedded filesystems, compressed archives, bootloaders, kernel images, and cryptographic material. Covers entropy analysis, recursive extraction, filesystem mounting, and string analysis for credential and configuration discovery.

Analyzes an HR operations system for headcount planning effectiveness, attrition pattern detection, compensation benchmarking accuracy, workforce analytics maturity, and onboarding process optimization. Evaluates HRIS architecture, pay equity compliance, predictive attrition models, and people analytics governance.

Access 83 unified crypto data endpoints covering CEX/DEX markets, on-chain SQL across 80+ blockchain tables, wallet labels, prediction markets, social intelligence, news, and DeFi metrics via a local HTTP API with per-call billing.

Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.

Provides code samples and best practices for using the Azure Tables SDK for Python to perform NoSQL key-value storage, entity CRUD, batch operations, and queries against Azure Storage Tables or Cosmos DB Table API.

Perform survival analysis and time-to-event modeling in Python using scikit-survival, including Cox models, random survival forests, gradient boosting, survival SVMs, and evaluation metrics like concordance index and Brier score.

Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.

Token budget analytics and ROI scoring for AI agent actions. Track token cost per fix, detect wasteful loops, auto-route to fast tier when burn rate is too high. Integrates with token-budget-guard.sh hook. Triggered by /cost-report, "how much did that cost", "token usage", "am I wasting tokens".

Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.

Calculates a per-ticker panic index (0-100) from six weighted signals including VIX, IV Rank, RSI-14, volume anomaly, put/call ratio, and consecutive down days, triggering Bull Put Spread entry signals at scores ≥60.

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

Provides 25 paid HTTP endpoints on Base mainnet that bill agents per call in USDC for web search, AI analysis, crypto and stock data, SEC filings, company intelligence, news, sentiment scoring, and a macro dashboard, returning structured JSON.

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

TikTok Shop e-commerce data assistant. Search products, find trending items, analyze influencers, explore shops, track video performance, and get ad insights via ecomseer.com. Triggers: 找商品, 搜商品, 爆品, 带货, TikTok电商, 达人分析, 视频带货, 店铺分析, 广告素材, 销量榜, 跨境电商, search products, find trending, TikTok Shop, influencer analysis, shop data, ad creatives, sales ranking, e-commerce analytics, product research.

Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies. Combines digital forensics, user behavior analytics, and HR/legal coordination to build an evidence-based case.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.

Logs and scores skill usage quality, tracking output effectiveness, user satisfaction signals, and improvement opportunities. Expert in skill analytics, quality metrics, feedback loops, and continuous improvement. Activate on "skill logging", "skill quality", "skill analytics", "skill scoring", "skill performance", "skill metrics", "track skill usage", "skill improvement". NOT for creating skills (use agent-creator), skill documentation (use skill-coach), or runtime debugging (use debugger skills).

After a Content Factory run completes successfully, harvest prompts, character references, cost data, and quality scores; diff them against the canonical prompt_registry and character_identity store; open improvement PRs (prompt updates + new character references). Runs ONCE per successful run, then closes. Also files findings into a CF_IMPROVER_ISSUES.csv (Intelliverse audit framework pattern) for the librarian's weekly roll-up.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Labor-hour and time-and-materials cost buildup with fully burdened hourly rates (BLS OEWS + GSA CALC+ + per diem MCPs). USE WHEN the user asks to "build a T&M IGCE", "labor hour estimate", "fully burdened hourly rate", "LH IGCE", "time and materials pricing", or "burden multiplier stack". Exports JSON + XLSX to Studio. DO NOT USE FOR FFP wrap rates (`igce-builder-ffp`), cost-reimbursement fee caps (`igce-builder-cr`), or OT bids (`ot-prototype-strategist`).