context-hunter
Context Hunter analyzes a codebase to identify established patterns, conventions, and implicit rules before implementing new features or changes. Use this skill when starting feature work, bug fixes, or refactoring to ensure new code matches existing approaches and discovers reusable utilities, naming conventions, schema patterns, and error handling strategies already present in the project.
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills /tmp/context-hunter && cp -r /tmp/context-hunter/bundled/skills/context-hunter ~/.claude/skills/context-hunterSKILL.md
# Context Hunter Before writing code, investigate how similar problems are already solved in this codebase. ## Before Implementation ### Discover Existing Patterns 1. **Find analogous features**: Search for code that solves similar problems. Study it before proposing your approach. 2. **Trace data flow**: How does similar data move through the system? Note caching, validation, and error handling patterns. 3. **Identify utilities**: Search for existing helpers before creating new ones. ### Detect Unwritten Conventions Look for implicit rules encoded in the codebase: - **Schema patterns**: `deleted_at` columns indicate soft-deletion. Audit columns indicate tracking requirements. - **Naming patterns**: Note consistency in `user_id` vs `userId` vs `userID`. - **Test patterns**: What's tested thoroughly reveals team priorities. ### Verify Assumptions - Run the test suite to understand current state - Check linter and formatter configs - Read recent commits in affected areas - Examine database schemas for constraints ## During Implementation ### Match Existing Code Your changes should be indistinguishable from existing code: - Use the same patterns, abstractions, and utilities - Follow the same error handling approach - Respect module boundaries - Match naming conventions exactly ### Surface Concerns When you discover conflicts between requirements and existing patterns: - Ask clarifying questions before proceeding - Flag risks you've identified - Offer alternatives that align with codebase conventions ## Checklist Before proposing changes, confirm: - [ ] Studied analogous features in the codebase - [ ] Checked for reusable utilities - [ ] Reviewed test patterns for similar functionality - [ ] Noted naming and schema conventions - [ ] Verified approach matches existing patterns
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Full-stack software development agent for design, implementation, testing, and deployment. Use when the user explicitly asks for end-to-end project creation, feature development, bug fixing, or code refactoring.
Unified biological database evidence owner. Use for gene annotation, variant clinical significance, cancer mutation evidence, GWAS trait associations, pathway mapping, target-disease evidence, protein structures, protein interaction networks, reference single-cell census queries, and cross-database biological ID mapping. Do not use for full single-cell analysis, bulk RNA-seq differential expression, BAM/VCF processing, protein embedding models, metabolic flux modeling, genomic interval ML, or flow-cytometry file parsing.