29 skills (repositories by AndrewBrown-USDA) · sorted by popularity
Distills enduring architectural decisions and design rationale from wave orchestration plans or historical git changes into structured, tracked Architecture Decision Records (ADRs). Use pre-wave to resolve active architectural constraints or post-wave to record enduring decisions in docs/decisions/.
The English summary is being prepared. Showing the original description.
Incrementally studies git history across tagged or pattern-matched intervals (e.g., creation of planning artifacts like EXECUTION_PLAN_N.md, release tags, or milestone commits). Extracts commit diffs, file churn, and subsystem shifts to track feature evolution and architectural convergence, providing structured feeds for ADR distillation.
The English summary is being prepared. Showing the original description.
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
The English summary is being prepared. Showing the original description.
Structured planning workflow for any coding task. Use at the start of every new feature, bug fix, refactor, or implementation request. Analyzes the project, asks up to 5 clarifying questions, creates a TODO.md, gets user approval, then executes task by task. Never writes code before a plan is approved.
The English summary is being prepared. Showing the original description.
GitHub Actions CI/CD setup for Python, R, and multi-platform testing. Use when creating, debugging, or optimizing CI/CD pipelines.
The English summary is being prepared. Showing the original description.
Captures web sources and compiles deterministic Markdown reference bundles with metadata and checksums. Use when asked to capture URLs, research web links, bundle search results, or archive web pages into an LLM-ready reference document.
The English summary is being prepared. Showing the original description.
Normalizes documentation and examples for consistency in style, format, and accuracy. Ensures code matches existing patterns and documentation. Use when reviewing docs, examples, or writing new code that should follow established patterns.
The English summary is being prepared. Showing the original description.
Standardizes Makefile-based build and test workflows with reproducible targets. Use when creating or refining helpful build, test, and clean targets.
The English summary is being prepared. Showing the original description.
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
The English summary is being prepared. Showing the original description.
Interactive guided walkthrough of code, line by line, where the agent reflects back your explanations without analysis. Use when debugging, reviewing, or understanding code by forced articulation.
The English summary is being prepared. Showing the original description.
Create and maintain AGENTS.md files for project onboarding and grounding. Use when initialized in a new project, when project structure changes significantly, or when creating subfolder-level AGENTS.md files for complex monorepos.
The English summary is being prepared. Showing the original description.
Audit and update an arbitrary codebase to follow the Code.mil federal open-source licensing model (MIT with 17 U.S.C. Section 105 disclaimers and INTENT.md), including CRAN/R package DESCRIPTION setup.
The English summary is being prepared. Showing the original description.
Ultra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".
The English summary is being prepared. Showing the original description.
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes - Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
The English summary is being prepared. Showing the original description.
Reads Copilot conversation history and extracts executive-ready success stories. Use when the user asks to study prior Copilot sessions, summarize what was done before, mine evidence, or quantify time, cost, risk, and priority alignment from GitHub Copilot history in any workspace or repository.
The English summary is being prepared. Showing the original description.
Installs skills from aigb-skills into a coding agent's skill directory. Use when setting up aigb-skills for Claude Code, Cursor, Copilot, or Pi.
The English summary is being prepared. Showing the original description.
Processes JSON on the command line with jq. Use when parsing, filtering, or validating JSON from files or APIs.
The English summary is being prepared. Showing the original description.
Design and run reproducible benchmarks. Use when measuring performance scaling, comparing branches, or analyzing speedup metrics.
The English summary is being prepared. Showing the original description.
Develops an implementation plan ready for wave-orchestration to execute. Takes the user's goal or rough plan as input, mines the codebase for facts, grills the user one question at a time for the decisions, drafts the planning/ artifacts (task DAG, wave table, worker prompt template, state file), then reviews its own plan on two axes before seeking approval. Use when the user wants to turn a feature idea, master plan, or backlog into a wave-orchestration execution plan.
The English summary is being prepared. Showing the original description.
Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).
The English summary is being prepared. Showing the original description.
Performs architectural code reviews focusing on design patterns, duplication, circular dependencies, and refactoring impact. Is the design consistent with the codebase? Use when reviewing code changes for architectural concerns, code smells, or structural issues.
The English summary is being prepared. Showing the original description.
Verifies bug fixes are correct and complete by tracing callers, checking imports/exports, validating path resolution, and confirming no regressions. Does the code work? Use when reviewing code changes for functional correctness.
The English summary is being prepared. Showing the original description.
Guides the discovery, design, validation, and delivery of Agent Skills. Use when identifying skill gaps, creating or revising a SKILL.md, improving skill descriptions, or checking a skill against the Agent Skills specification.
The English summary is being prepared. Showing the original description.
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
The English summary is being prepared. Showing the original description.