Manage a local task/backlog list (tasks.json + a generated TASKS.md) for the current repo and reconcile it with GitHub or Gitea issues, via the bundled task-sync Python tool. Supports direct commands (list/add/edit/done/remove/ status/init) and a plan-decide-apply sync that surfaces creates, pushes, pulls, conflicts, and confidentiality findings for review before anything leaves the machine, with a public-repo push warning and a --dry-run mode. Suggest when — the user wants to see or manage this repo's tasks or backlog, sync tasks with GitHub/Gitea issues, mentions a local task tracker or TASKS.md, or asks to push/pull/reconcile tasks against issues; keywords — task list, backlog, sync issues, task-sync, todo list, reconcile issues.
Initialize mandatory experiment logging using scientific notebook, ADR, and postmortem patterns. For projects involving system changes, benchmarks, debugging, or exploratory work. Creates LAB_NOTEBOOK.md with living decision/action tracking and injects iron-clad CLAUDE.md rules that make logging a PRECONDITION for every action. Suggest (do not auto-run) when — infrastructure/experimental/expensive-failure projects, multi-session work, or keywords like optimize/benchmark/debug/configure.
Generate BPMN 2.0 compliant XML files from natural language process descriptions OR from structured markdown business process documents. Use this skill when a user wants to create a BPMN workflow, convert a business process to BPMN XML, model a workflow diagram, or generate process definitions. Triggers on requests like "create a BPMN", "generate workflow XML", "model this process", "convert to BPMN 2.0", "create process diagram", "build workflow", or "convert this markdown to BPMN". Do NOT use for converting an existing BPMN XML file to Draw.io — use bpmn-to-drawio for that.
Analyze technical documents for CS/ML concepts a smart non-CS reader wouldn't understand, recommend explanation mechanisms (glossary, inline, footnote, sidebar, appendix), present analysis for approval, then implement annotations in the Word document using the project directory for contextual accuracy. Use when making technical documents accessible to non-CS audiences. Do NOT use for writing a new overview document from a codebase — use explain-project for that.
Comprehensive 9-agent architecture review — spawns parallel domain specialists (architecture, code, data, integration, performance, QA, security, platform, risk) and produces structured findings with executive report and go/no-go recommendation
Set up a persistent, LLM-maintained wiki inside any project. Creates a wiki/ directory with sources, pages, schema, and navigation files, seeds initial pages from project discovery, and injects CLAUDE.md rules that make Claude automatically maintain the wiki during normal work sessions. Suggest (do not auto-run) when — project accumulating complexity, context loss between sessions, multiple contributors, "I keep forgetting", significant domain knowledge, or LAB_NOTEBOOK.md with durable insights.
Thoroughly evaluate contact-center-lab pipeline output quality against input, checking sanitization correctness, atom/entity/triple quality, graph structure, and procedure integrity across all stages. Suggest when — pipeline run complete and quality evaluation needed, "did this produce good output" questions, before full corpus run, or after pipeline code changes.
Generate a comprehensive, annotated technical overview document for any project/repo, written for a smart non-CS reader. Analyzes the codebase, writes a deep-dive document following a proven structure template, and produces a styled Word document with sidebars, glossary, inline annotations, and optional generated images. Use when a project needs an explanatory document that makes the system understandable to non-technical stakeholders. Do NOT use for annotating an EXISTING document — use accessibility-annotator for that. Do NOT use for plain markdown-to-Word formatting with no annotations — use /convert-markdown for that.