agent-skills-mirror

Use when the user requests diagrams, flowcharts, architecture diagrams, ER diagrams, UML / sequence / class diagrams, network topology, cloud architecture from Terraform or Kubernetes manifests, ML/DL model figures (Transformer/CNN/LSTM), mind maps, or any visualization. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Best suited when the diagram needs custom styling, rich shape vocabulary, swimlanes, or exportable images (PNG/SVG/PDF/JPG). Generates .drawio XML and exports locally via the native draw.io desktop CLI.

Catalog of the AO (Agent Orchestrator) `ao` CLI: spawning workers, managing sessions and projects, sending messages, previewing pages, and daemon control. Use when using the ao CLI, spawning workers, or managing AO sessions in an AO workspace.

FALLBACK ONLY — do not invoke unless you have already ruled out (1) a native API (Gmail API, GitHub API, Slack API …), (2) a CLI (git, gh, aws, npm, curl …), (3) direct file editing, and (4) existing browser automation (Playwright, Puppeteer). Only when all four are unavailable or have already failed should you use this skill. It gives AI agents a cursor and a keyboard on a real desktop — the last mile when the only remaining surface is a GUI. Concretely: use it when an earlier attempt via API, CLI, or direct file edit has failed and the user says things like "open X", "click Send", "type this in Word", "read what is on my screen", "do this in Outlook", "drive the Figma UI", "control my desktop", "automate this workflow", "fill out this form", or "copy text between apps". Works on Windows, macOS, and Linux with any LLM that can call functions (Claude, GPT, Gemini, Llama, Kimi, Ollama) over MCP — stdio for editor hosts (Claude Code, Cursor, Windsurf, Zed) or HTTP for daemons and dashboards.

FALLBACK ONLY — do not invoke unless you have already ruled out (1) a native API (Gmail API, GitHub API, Slack API …), (2) a CLI (git, gh, aws, npm, curl …), (3) direct file editing, and (4) existing browser automation (Playwright, Puppeteer). Only when all four are unavailable or have already failed should you use this skill. It gives AI agents a cursor and a keyboard on a real desktop — the last mile when the only remaining surface is a GUI. Concretely: use it when an earlier attempt via API, CLI, or direct file edit has failed and the user says things like "open X", "click Send", "type this in Word", "read what is on my screen", "do this in Outlook", "drive the Figma UI", "control my desktop", "automate this workflow", "fill out this form", or "copy text between apps". Works on Windows, macOS, and Linux with any LLM that can call functions (Claude, GPT, Gemini, Llama, Kimi, Ollama) over MCP — stdio for editor hosts (Claude Code, Cursor, Windsurf, Zed) or HTTP for daemons and dashboards.

Use when you need to ask questions about a codebase or understand code using a knowledge graph

Launch the interactive web dashboard to visualize a codebase's knowledge graph

Extract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.

Use when you need a deep-dive explanation of a specific file, function, or module in the codebase

Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Use when a task is multi-step, may span context resets or sessions, uses subagents, or risks losing state before completion.

Use when about to claim work is complete, fixed, passing, verified, release-ready, or ready to commit, merge, publish, or hand off.

Use when you have a spec or requirements for a multi-step task, before touching code

One-time setup wizard for the nanobot upgrade skill. Triggers: setup update, configure update, 切设置更新, 初始化更新.

Decision guide for delegating to caveman-style subagents. Tells the main thread WHEN to spawn `cavecrew-investigator` (locate code), `cavecrew-builder` (1-2 file edit), or `cavecrew-reviewer` (diff review) instead of doing the work inline or using vanilla `Explore`. Subagent output is caveman-compressed so the tool-result injected back into main context is ~60% smaller — main context lasts longer across long sessions. Trigger: "delegate to subagent", "use cavecrew", "spawn investigator/builder/reviewer", "save context", "compressed agent output".

Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress FILEPATH or "compress memory file"

Triage bugs reported in chat/issues, search for duplicates, file or update GitHub issues with full context, and push fix PRs.

Augment a Wren project with business context that DB schema cannot carry — enum value meanings, units (USD vs cents, ms vs sec), NULL semantics, magic sentinels (-1 = unknown), soft-delete default filters, business synonyms, time-grain / TZ conventions, cross-system identifiers, currency rules, canonical-table preferences, AND named aggregation metrics (ARR, churn, DAU, WAU, NRR) proposed as cubes. Runs in one of two modes selected at session start: `grill` (one question at a time, user-driven) or `auto-pilot` (agent infers and applies, escalates only on conflicts and high-blast-radius additions like new cubes / views / relationships). Reads everything under <project>/raw/ (PDFs, glossaries, handbooks, code, data dictionaries) and optionally samples low-cardinality columns from the live DB (grill mode), compares against the current MDL / cubes / knowledge (rules + NL→SQL pairs), then fills gaps via the ten-category gap catalog and the cube proposal flow. Confirmed findings are written back to the right sink.

Turn a Wren project's context layer into a shareable, browser-side GenBI web app and deploy it to the user's Vercel or Cloudflare account. Orchestrates the full flow: `wren genbi build` returns a project-hydrated build instruction, the agent authors the app from scratch into apps/<name>/, then register → verify → deploy produce a shareable URL. Use this skill whenever the user wants to: build a dashboard from their Wren project, make a shareable analytics app, deploy their context layer as a web app, host a GenBI app on Vercel or Cloudflare Pages, or asks for a 'genbi app'.

Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.

Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a share

Manage persistent coding sessions across Claude Code, Codex, Gemini, Cursor, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, or exposing the orchestrator's 65 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "deep paper review", "auto research", "switch model", "multi-agent", "coding session", "session inbox", "cursor agent", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol

Use when the user says `aegis:update`, asks to update or upgrade an installed Aegis method-pack, wants the latest Aegis version, or asks whether Aegis is current on this host.

Use when starting a turn or checking Aegis skill routing.

Create polished design artifacts as self-contained HTML: UI mockups, interactive prototypes, wireframes, landing pages, dashboards, app screens, mobile apps, slide decks (a.k.a. PPT / PowerPoint presentations), and visual explorations. Use whenever the user asks to design, mock up, prototype, wireframe, visualize, explore, or make a PPT/deck for an interface, product screen, user flow, content layout, visual artifact, or pitch/deck concept, even if they do not say "design". Also use to export a deck built with this skill to PowerPoint (PPT/PPTX) — but only decks authored here (deck-stage / this skill's slide-structured HTML), NOT arbitrary HTML, so confirm the target is such a deck first. Also use for setting up, importing, or authoring reusable design systems, UI kits, brand tokens, or component libraries. Harness-agnostic for Claude Code, Cursor, Codex Agent, and similar file-capable agents.

Summarizes WeChat group chat highlights into a structured digest using the local wx-cli binary (https://github.com/jackwener/wx-cli). Generates a normal digest by default; a roast (毒舌) version is opt-in. Maintains per-group history (history.json + history-digests.jsonl), per-user profiles, and per-group fact memory (memory.md) across runs, with privacy guardrails baked in. Use when the user asks to "总结群聊", "群聊精华", "群聊摘要", "summarize group chat", "group chat digest", mentions a WeChat group name with a time range, says "帮我看看 XX 群最近聊了什么", "XX 群有什么值得看的", or asks to "回溯画像" / "初始化画像" / "backfill profiles". Adds the roast version when the user says "毒舌版", "roast 版", "再来个毒舌的", or similar.

Quick reference for ponytail's modes, skills, and commands. One-shot display.

Use when retiring old logic, collapsing duplicate owners, removing fallbacks, or touching schema, persistence, or source-of-truth boundaries while deciding whether to delete old paths, retain compatibility, or stop for confirmation.

Use when defining new features, product behavior, UI/component design, architecture choices, contract changes, or ambiguous medium/high-complexity work before implementation.

Use when the user explicitly asks for first principles, first-principles review, Occam's razor, or when a complex decision has ambiguous goals, competing constraints, repeated fixes, fallback growth, duplicate owners, or architecture/product direction risk.

Use when the user explicitly sets an Aegis goal with /aegis-goal, Aegis goal:, or asks to define goal, success evidence, stop condition, or task boundaries before work.

Use when the user asks to create, write, update, amend, supersede, or evaluate an ADR, architecture decision record, durable architecture decision, decision log, or baseline sync after architecture-changing work.

Use when explicitly requesting an independent code review, after subagent-driven implementation slices, before merging high-risk work, or when verification finds evidence, baseline, architecture, compatibility, or retirement uncertainty that needs reviewer scrutiny.

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Use when the user explicitly requests strict or test-first TDD, or when the current conversation already contains an explicit `TDD Route: strict` decision from another Aegis workflow.

Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.

Ingest any source into the Obsidian wiki by distilling its knowledge into interconnected wiki pages. Handles structured documents (PDFs, markdown, articles, papers, notes, folders), raw/unstructured text (chat exports, conversation logs, Slack/Discord threads, meeting transcripts, CSV/JSON data, journal entries, browser bookmarks, email archives, text dumps), AND web URLs. Use whenever the user wants to add new sources to their wiki: "add this to the wiki", "process these docs", "ingest this folder", "ingest this data", "process this export/logs", "import my chat history from X", "/ingest-url <url>", "add this URL", "save this page", or pastes a URL and says "add this" / "save this to my wiki". Also triggers when the user drops a file, or for raw mode: "process my drafts", "promote my raw pages", or any reference to the _raw/ staging directory. This is the general catch-all ingest skill for any document, text, or URL source not covered by a more specific ingest skill (claude-history-ingest, etc.).

Classify structural variants / copy-number variants (deletions and duplications) using the ClinGen / ACMG 2019 (Riggs et al. 2020) point framework and return a five-tier classification with a per-section evidence trail. Germline CNV interpretation, not SNV/indel.

Hand off a model from Blender (via BlenderMCP) into Unity (via MCP for Unity) — export the current Blender model, import it through import_model_file, and place it in the open scene. Use when the user has BlenderMCP and MCP for Unity both connected and wants to bring a Blender model into Unity. Does NOT drive Blender's own generators; BlenderMCP owns how the model got into Blender.