AnEntrypoint

Generate system architecture diagrams as Mermaid, PlantUML, or ASCII art from a description or codebase

Convert images or video frames to ASCII art, or generate ASCII animations from descriptions

Generate concept maps, mind maps, and ER diagrams from free-form descriptions

Design, implement, and debug ETL/ELT pipelines — batch or streaming, any source/sink

Explain SQL queries, execution plans, and performance issues in plain English with rewrites

Guide incident response: triage, diagnosis, mitigation, communication, and post-mortem

Triage application and system logs to find root causes, anomalies, and error patterns

Draft Objectives and Key Results from goals, strategy docs, or free-form priorities

The primary driver for any non-trivial coding, refactoring, debugging, or multi-step engineering task in a project using this harness -- use it first, for the whole task, not just a piece of it. Plugkit-served instruction stream. Three-layer admission (witness, single-writer, direction) over every possible mutation; effort unbounded, never gated on cost. Closure on first emit; partial = non-monotonic. Not for the post-completion remaining-work check (that is `gm-continue`) or for drift-recovery mid-task (that is `wfgy-method`) -- this skill is the work itself.

WFGY 5.0's core problem-solving tool. Lifts targets into higher problem-coordinates and returns structured routes (proof paths, strategy kernels, research structures, repair paths, positioning routes). Theorem work to everyday decisions. Use after Goal Compiler to execute the compiled problem specification.

A human-AI communication protocol layer that compiles goals into task atoms, active/blocked work, verification gates, and claim ceilings before execution. Part of WFGY 5.0 Polaris Protocol. Use before complex AI work to make it inspectable, harder to fake, and less likely to collapse into premature completion.

WFGY 5.0 Polaris Protocol -- the active flagship route from onestardao/WFGY. A two-layer reasoning system that compiles goals before execution and shoots complex problems into inspectable routes, with drift control throughout. This skill is the tree root: load it first, then dispatch its child skills as explicit transitions -- polaris-goal-compiler (compile), fifth-dimension-engine (shoot), wfgy-method (drift control). Use for any complex, multi-step, high-stakes, or long-horizon task where premature completion or goal drift is a risk.

Applies WFGY (Wan Fa Gui Yi), a portable reasoning discipline for reducing drift and incoherence across multi-step agent work, adapted from onestardao/WFGY's core mechanism. Compares each step against the stated goal, considers more than one approach before committing to ambiguous or high-stakes decisions, and checkpoints before risky steps so it can revert and bounded-retry instead of compounding a mistake. Records durable lessons in this project so future sessions inherit them. Use when starting any non-trivial multi-step task, when a task risks losing track of its original goal over many steps, when facing a decision with real alternatives worth comparing, or when the agent notices it has contradicted itself or gone in circles and needs a disciplined way to recover. Distinct from `gm-continue`: that skill is the post-`gm`-COMPLETE remaining-work check; this skill is the general drift-recovery discipline `gm-continue` invokes when a `gm` walk repeats the same gap -- not a substitute for its check.

The mandatory final handoff after a gm walk reaches phase=COMPLETE with prd_pending_count=0. Never end a gm session with prose alone -- dispatch this skill instead. It searches for genuinely remaining work and reloads gm if any exists; if gm already ran a full walk without resolving everything, it loads wfgy-method instead to apply bounded-retry-then-surface discipline before any further gm re-entry. Use immediately after any gm chain reaches its terminal state, never as a substitute for gm itself.

Open-ended research over the semiosis cone KB. You are handed questions you cannot answer from where you sit; you go look, bring back what you actually found, and say how sure it leaves you. Doing this turn after turn is the work. Use whenever a task is exploration rather than a single lookup.

Drive the semiosis KnowledgeBase: hyperbolic entailment cones over Matryoshka octaves. Use it whenever a task requires semantic search, hierarchy navigation, context packing, or KB health management. The KB is the single source of truth for meaning; state carried only in prose is lost on restart.

Plugkit-served instruction stream. Three-layer admission (cost, bounds, direction) over every mutation. Closure on first emit; partial = non-monotonic.

Build multiplayer physics games with the Spoint engine. Use when asked to: create a game, add physics objects, spawn entities, build a map/level, handle player interaction, add weapons, respawn, scoring, create moving platforms, manage world config, load 3D models, add HUD/UI, work with the EventBus, or develop any app inside an apps/ directory.

Persistent memory and recall, wasm-only. Compiled to wasm32 and consumed by rs-plugkit; no native CLI, no MCP server, no HTTP. Activate when the user wants to remember facts across sessions, recall prior context mid-task, or wire an agent to a queryable knowledge store. Dispatched via plugkit spool verbs `recall` and `memorize`. Per-discipline isolation under `<project>/.gm/disciplines/<name>/rs-learn.db`. Embeddings 384-dim (MiniLM-L6-v2).

Google Workspace operations — Docs, Sheets, Drive, Apps Script, Gmail, Calendar, Tasks, Slides, Contacts, Chat, and Search. Use for creating, reading, editing Google Docs/Sheets/Slides. Use for Drive file management. Use for Calendar events and scheduling. Use for Gmail messages, labels, and filters. Use for Tasks, Contacts, and Chat.