Research

Use when generating, updating, or organizing documentation (component/API docs, project indexes, diagrams, tutorials, learning paths) - provides structured workflows and references for docs generation, indexing, diagrams, and teaching.

The model must use this skill when : 1. working within any python project. 2. Python CLI applications with Typer and Rich are mentioned by the user. 2. tasked with Python script writing or editing. 3. building CI scripts or tools. 4. Creating portable Python scripts with stdlib only. 5. planning out a python package design. 6. running any python script or test. 7. writing tests (unit, integration, e2e, validation) for a python script, package, or application. Reviewing Python code against best practices or for code smells. 8. The python command fails to run or errors, or the python3 command shows errors. 9. pre-commit or linting errors occur in python files. 10. Writing or editing python code in a git repository.\n<hint>This skill provides : 1. the users preferred workflow patterns for test-driven development, feature addition, refactoring, debugging, and code review using modern Python 3.11+ patterns (including PEP 723 inline metadata, native generics, and type-safe async processing). 2. References to favor

AshPostgres data layer guidelines for PostgreSQL with Ash Framework. Use when configuring postgres blocks, foreign key references, check constraints, custom indexes, migrations, or multitenancy. The default choice for Ash data layers. Supports PostgreSQL 13+.

Create an interactive educational MicroSim using the p5.js JavaScript library with distinct regions for drawing and interactive controls. Each MicroSim is a directory located in the /docs/sims folder. It has a main.html file that references the javascript code and the main.html can be referenced as an iframe from the index.md. The metadata.json contains Dublin core metadata about the MicroSim.

This skill should be used when conducting comprehensive research on any topic using the OpenAI Deep Research API. It automates prompt enhancement through interactive clarifying questions, saves research parameters, and executes deep research with web search capabilities. Use when the user asks for in-depth analysis, investigation, research summaries, or topic exploration.

Develop Zellij plugins with Rust/WASM, API reference, event system, UI rendering, plugin lifecycle, and real-world examples from diverse open source plugins

Systematic technical research combining multi-source discovery with evidence-based analysis. Delivers authoritative recommendations backed by credible sources. Use when researching best practices, evaluating technologies, comparing approaches, discovering documentation, troubleshooting with authoritative sources, or when research, documentation, evaluation, comparison, or `--research` are mentioned.

Planning specialist that creates structured implementation plans for the finans project. Use this skill to transform user requests into comprehensive, well-researched plan files stored in .task-board/backlog/. This skill plans without implementing.

Research-driven critique and enhancement of Amelia architecture or ideas docs. Use with GPT-5.2 when given a design/architecture doc to analyze concepts, find sources, and propose improvements plus OSS candidates.

ChatGPT-style deep research strategy with problem decomposition, multi-query generation (3-5 variations per sub-question), evidence synthesis with source ranking, numbered citations, and iterative refinement. Use for complex architecture decisions, multi-domain synthesis, strategic comparisons, technology selection. Keywords: architecture, integration, best practices, strategy, recommendations, comparison.

This skill converts text to high-quality audio files using ElevenLabs API. Use this skill when users request text-to-speech generation, audio narration, or voice synthesis with customizable voice parameters (stability, similarity boost) and voice presets (rachel, adam, bella, elli, josh, arnold, ava).

Excavate session logs for provenance tracking. TRIGGERS - who created, document finding, trace origin, session archaeology, provenance, ADR reference.

When creating a README for a Python package. When preparing a package for PyPI publication. When README renders incorrectly on PyPI. When choosing between README.md and README.rst. When running twine check and seeing rendering errors. When configuring readme field in pyproject.toml.

Professional PDF generation from markdown using Pandoc with Eisvogel template and EB Garamond fonts. Use when converting markdown to PDF, creating white papers, research documents, marketing materials, or technical documentation. Supports both English and Russian documents with professional typography and color-coded themes. Mobile-optimized layout (6x9) by default for Telegram bot context, desktop/print layout (A4) for other contexts.

Log experiment metrics, parameters, and artifacts using MLflow Python API. Query and analyze runs with DataFrame operations. Use when user mentions "log backtest", "MLflow metrics", "experiment tracking", "log parameters", "search runs", "MLflow query", or needs to record strategy performance.

Diagnose research quality and guide systematic query expansion. Use when starting research on any topic, when stuck in research, or when unsure if research is complete.

Write technical blog posts with source code analysis OR doc-driven research. Use when user wants to explain system internals, architecture, implementation details, or technical concepts with citations.

Analyze conversation history to identify patterns, signals, and behaviors. Use when analyzing conversations, finding patterns in chat, identifying what went well/wrong, scanning for frustration, success, workflow transitions, or user preferences. Triggers on analyze, pattern(s), signal(s), conversation analysis, or `--analyze-conversation`.

Standard multi-source verification search strategy for moderate complexity research. 2-iteration workflow with source ranking, consensus identification, and citation transparency. Use for feature comparisons, moderate complexity topics, fact-checking. Keywords: compare, differences, features, fact-check, verify, what are.

Network protocol analyzer and packet capture tool for traffic analysis, security investigations, and forensic examination using Wireshark's command-line interface. Use when: (1) Analyzing network traffic for security incidents and malware detection, (2) Capturing and filtering packets for forensic analysis, (3) Extracting credentials and sensitive data from network captures, (4) Investigating network anomalies and attack patterns, (5) Validating encryption and security controls, (6) Performing protocol analysis for vulnerability research.