18 skills published by ReinaMacCredy across 1 repository. Together they weigh 88 818 tokens — that is what loading all of them at once would cost you in context.
18 skills 88 818 tokens total
Router for choosing the next Maestro skill or lifecycle recipe.
>- flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the user mentions agents, terminals, or automation-friendly CLIs.
>- Update repository documentation to match the current state of the codebase. Local replacement for the remote /docs command (which needs the Claude GitHub app). Use when the user says /docs, "update the docs", "sync the README", "document this feature", or asks you to refresh docs to reflect current code. Works inline in the current session and edits files in the working tree.
Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: \"Index this repo\", \"Reanalyze the codebase\", \"Generate a wiki\
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: \"Why is X failing?\", \"Where does this error come from?\", \"Trace this bug\
Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: \"How does X work?\", \"What calls this function?\", \"Show me the auth flow\
Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: \"What GitNexus tools are available?\", \"How do I use GitNexus?\
Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: \"Is it safe to change X?\", \"What depends on this?\", \"What will break?\
Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: \"Rename this function\", \"Extract this into a module\", \"Refactor this class\", \"Move this to a separate file\
Audit a project using Maestro read-only: use for code review, architecture review, deepening opportunities, backlog proposals, harness-improvement findings, or repo-wide improvement audits without fixes.
Card work in a project using Maestro after design approval: use for implement, fix, verify, QA, close, release, continue, or unattended prompts like use loop, keep looping, work while away/asleep.
Design in a project using Maestro before implementation: use for brainstorm, plan, PRD synthesis, grilling/stress-test, domain model, deepening candidate, wording, workflow, skill/harness, card/task/feature, architecture, UX, or agent-process decisions.
Pre-design research for Maestro cards: creates or validates a same-card research.md receipt, maps context, stakeholders, hosting, unknowns, and the first design fork. Use before maestro-design when the user brings a new idea, zero-context feature, external/pasted plan, unfamiliar domain, stakeholder-heavy request, hosting-unclear work, or when research is missing, stale, skipped-risky, or needed for READY_FOR_DESIGN.
Setup Maestro in a project using or adopting Maestro: use for init/install/sync/doctor, global skills, hooks, harness setup, or agent integration diagnosis/repair.
Witness feature close: use after Maestro feature proof and QA pass, before feature close, to write current witness.md/advisor.md receipts, auto-invoke an independent advisor when allowed, apply risk-tier and human-demo policy, and emit Gate: APPROVED.
>- tools, flat constrained parameters, actionable errors via isError, token-efficient responses, composable outputs, and disciplined tool surfaces. Use when building an MCP server, adding tools to one, reviewing MCP tool design, or when the user mentions MCP optimization, tool descriptions, MCP best practices, or agent-friendly MCP design. Also use when the user has too many tools causing agent confusion, bloated responses wasting tokens, or agents picking the wrong tool.
Strengthen a raw user prompt into an execution-ready instruction set for Amp, Claude Code, Codex, or another AI agent. Use when the user wants to improve an existing prompt, build a reusable prompting framework, wrap the current request with better structure, add clearer tool rules, or create a hook that upgrades prompts before execution.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).