poorrican
16 verified skills
using-nautilus-trader
Provides expert guidance for NautilusTrader algorithmic trading platform. Covers backtesting strategies, live trading deployment, event-driven architecture, and building trading systems.
development
codex
Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing
tools
stacked-issues
Implement multiple GitHub issues sequentially as stacked branches in separate worktrees, with an implementer sub-agent and an independent reviewer sub-agent per issue. Use when the user gives you two or more dependent issues and asks for them to be implemented in order, or says "stacked branches", "sequential issues", "issue chain", "do these in worktrees", or describes a parent epic with child issues that build on each other. Also reach for this whenever the user wants implementation and verification done by separate agents.
development
feature-brainstorm
Multi-phase brainstorming for complex feature implementations using parallel sub-tasks. Use when the user asks to brainstorm, design, or plan a complex feature, wants to explore implementation approaches, or needs architectural analysis before coding. Triggers on phrases like "brainstorm feature", "design implementation", "explore approaches", "plan architecture", or "how should we implement".
data-ai
experiment-log-interview
Conducts a structured Socratic interview to produce or update a single experiment log entry — the durable record of what was run, what it showed, and what it means. Use this skill whenever the user wants to log an experiment, write up results, record a backtest, capture a finding, pre-register a run, document a study, or update an existing entry with new results or a revised interpretation. Trigger on phrases like "log this experiment," "write up the results of...", "I ran X, help me document it," "pre-register this," "update the entry for...", or when the user shares results and asks for help interpreting and recording them. The skill enforces the four-way separation between what happened, what it means, what it implies, and what comes next; challenges the user's interpretations with evidence requests and alternative explanations; and writes incrementally to keep context clean and the entry always grounded.
testing
research-proposal-structure
Use when an agent needs to produce, update, validate, or normalize a standardized research proposal artifact without running an interview. Defines the canonical structure, confidence-tag semantics, decision logic, and completion checks for proposal.md-style research plans.
testing
experiment-log-structure
Use when an agent needs to produce, update, validate, or normalize a standardized experiment-log entry without running an interview. Defines the canonical structure, pre-registration rules, evidence/interpretation split, calibration tags, and append-only revision model for durable experiment records.
testing
research-proposal-interview
Conducts a structured Socratic interview to produce a comprehensive markdown research proposal that handles cascading uncertainty (fixed end-question, branching experiments). Use this skill whenever the user wants to write a research proposal, research plan, study design, experiment plan, thesis proposal, RFC, or "spec out" a research direction — even if they don't explicitly say "interview me." Trigger when the user says things like "help me plan this research", "I want to design experiments for X", "draft a proposal for...", "think through a research direction", or shares a half-formed research idea and asks for help structuring it. The skill interviews the user, challenges their priors with evidence requests and falsifiers, optionally uses sub-agents to explore prior art, and builds the proposal markdown incrementally so context stays clean and the document is always grounded.
development
using-proton-pass-cli
Interact with Proton Pass via the `pass-cli` command-line tool. Use this skill when the user wants to manage passwords, vaults, items, SSH keys, secret injection, or any credential management through the Proton Pass CLI. Triggers on mentions of pass-cli, proton pass, secret references, pass:// URIs, vault management, or SSH agent integration with Proton Pass.
tools
analyzing-backtests
Analyzes algorithmic trading backtest results from Jupyter notebooks and generates summary reports. Use when the user wants to analyze or summarize backtest notebooks.
development
brainstorm
Adversarial brainstorming partner that pressure-tests ideas, challenges assumptions, and explores the codebase to arrive at well-architected solutions. Use when the user asks to brainstorm, challenge an idea, explore approaches, pressure-test a design, or think through architecture. Triggers on phrases like "brainstorm", "challenge this", "pressure test", "what if", "should we", "is this the right approach", "explore alternatives".
development
conventional-commits
Commit changes in a git workspace using the Conventional Commits specification. Use when the user asks to commit, stage, or save changes to git, or mentions "conventional commits". Analyzes staged/unstaged changes, groups related modifications, generates properly formatted commit messages, and commits files separately or together as appropriate. Confirms with user when commit ordering is ambiguous.
development
data-juicer
Primer for using the data-juicer Python library (also written `datajuicer` or `DJ`) — a YAML-driven, OP-based system for cleaning, filtering, deduplicating, transforming, and synthesizing text and multimodal data for foundation models. Use this skill whenever the user mentions data-juicer, DJ, dj-process, dj-analyze, "DJ format", building data recipes / YAML pipelines for LLM training data, or writing custom Filter / Mapper / Deduplicator / Selector / Aggregator / Grouper operators ("OPs"). Also reach for it when the user is putting together a data preprocessing pipeline for LLM pre-training, post-tuning, or multimodal datasets and DJ would be a natural fit, even if they haven't named the library yet — flagging DJ as an option is often the most helpful move.
development
manage-dotfiles
Manage dotfiles and keep synced with external directories. Use on Linux / macOS systemswhen thetre are external connfigs which are being imported into the dotfiles, or when stored dotfiles need to be brought outside to the XDG environment.
tools
package-skill
Package a Claude Code skill directory into a distributable .skill file. Use when the user wants to export, package, bundle, zip, or distribute a skill. Triggers on mentions of .skill files, packaging skills, exporting skills, or sharing skills.
development
stacked-prs
Push local branches and create stacked PRs. Analyzes branch topology, pushes, creates PRs with correct base branches, and resolves merge conflicts. Use when you have a chain of local branches to turn into stacked PRs.
data-ai