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Found 1,406 Skills
Specialized agent for developing JSUI applications. Invoke when writing JSUI code, needing API references for jsui/wx, debugging JSUI applications, or aligning JSUI visual design with this Skill's design guidelines.
Audit a python-pptx export against its source HTML deck, identify layout/content drift (footer overflow, cropped content, missing italic/em, lost styling, off-rhythm spacing), and re-export with strict footer-rail + cursor-flow layout discipline. Use this skill whenever the user has a .pptx that was generated from an HTML slide deck and asks to compare/audit/verify/fix the export — including phrases like "compare ppt with html", "fidelity audit", "fix the pptx", "ppt is cut off", "footer overlap", "italic missing in pptx", "re-export the deck", "pptx-html-fidelity-audit", or any case where a python-pptx → HTML round-trip needs verification or repair. Also trigger when the user shows you a deck.html and a deck.pptx side by side and is debugging visual differences.
This skill should be used when the user wants to create a new agent skill, scaffold a SKILL.md, validate an existing skill against repo rules, or refactor a skill to match this monorepo's conventions. Common triggers include "build a skill for X", "create a new skill", "scaffold a skill", "add a skill that does Y", "make me a skill", "audit this skill against our rules", and "refactor this skill to match repo conventions". Enforces kebab-case naming, verbatim trigger phrases, selective XML for example boundaries, and a RED→GREEN→REFACTOR cycle. Skip when modifying source code, debugging an existing skill, or writing non-skill markdown.
Expert guide for Next.js 14+ App Router projects. Use when building features, routing, server/client components, forms, layouts, or debugging Next.js-specific issues.
Stateful LLDB debugging via LLDB Python API
Converts cuTile GPU kernels (@ct.kernel) to Triton (@triton.jit). Handles standard in-repo conversion, debugging (cudaErrorIllegalAddress, shape mismatch, numerical mismatch), and mapping cuTile idioms (ct.load/ct.store, ct.Constant, ct.launch) to Triton equivalents. Covers dual-kernel layout flags (e.g. transpose=True/False + autotune grid via META) per translations/advanced-patterns.md. Use when converting, porting, or translating cuTile kernels to Triton, or debugging existing Triton translations.
Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning. Covers tile sizes, occupancy, autotune configs, TMA, latency hints, persistent scheduling, num_ctas, flush_to_zero, and IR-level debugging. Use when asked to "optimize cutile kernel", "improve kernel perf", "tune cutile performance", "make kernel faster", or iteratively benchmark and refine a cuTile GPU kernel in the TileGym project.
Use when a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding, expense reimbursement, system-access provisioning, customer-escalation playbook) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, ops onboarding doc generation, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Kaoru Ishikawa's 5W2H method, Atul Gawande's *The Checklist Manifesto*, ISO 9001, ITIL v4 Service Operation, FDA 21 CFR Part 211, and Google SRE Workbook runbook discipline with deterministic stdlib-only Python tools that score completeness, detect anti-patterns, and emit prioritized cleanup lists. Distinct from `engineering/llm-wiki` (Karpathy-style personal PKM second brain), `engineering-team/runbook-generator` (system-ops production debugging runbook), `project-management/*` (Jira/Confluence delivery + ticket tracking), and sibling `business-operations/process-mapper` (BPMN process *design*, while knowledge-ops is process *documentation*).
Debug Android WebView, browsers, and Node.js using Chrome DevTools through FoldDevtools with root or remote debugging
Invoke the `groundcover` Go CLI to manage Groundcover resources (dashboards, monitors, silences, connected apps, notification routes, API keys, policies, integrations, pipelines, workflows) AND to answer production observability questions by querying logs, traces, metrics, k8s inventory, and k8s events. Use whenever a task needs an authenticated call against the Groundcover API or whenever the user is debugging a prod issue and asks things like "why is X erroring in prod", "show me logs for service Y", "what's the p99 latency on Z", "what pods are crashlooping", "search traces for slow requests", "any k8s events for namespace N", "is service S receiving traffic", "list groundcover monitors", "create a silence", "update notification route", "hit a groundcover endpoint". Covers required env vars, the SDK-backed vs raw command split, and concrete request-body templates for logs/traces/metrics/k8s so the CLI can be driven from anywhere.
Structure a pygame (pygame-ce) game in Python: the init/event/update/draw loop, delta-time movement, Surface/Rect blitting, keyboard/mouse input, and Sprite/Group management with collision. Use when building or debugging a pygame game — when the user mentions pygame, pygame-ce, the game loop, blit, Surface, Rect, sprite groups, or clock.tick. Targets pygame-ce.
Add persistent, structured long-term memory to AI agents using Maximem Synap. Use this skill whenever the user is building, debugging, or evaluating an AI agent and mentions any of: "memory", "long-term memory", "persistent memory", "agent memory", "remember across sessions", "context window", "agent forgets", "user preferences", "personalization", "RAG over conversations", "multi-tenant memory", "memory layer", "Mem0", "Zep", "Letta", "SuperMemory", "Cognee", or asks how to integrate memory into LangChain, LangGraph, LlamaIndex, OpenAI Agents SDK, Pydantic AI, CrewAI, AutoGen, Google ADK, Haystack, Agno, Semantic Kernel, Microsoft Agent Framework, NVIDIA NeMo, LiveKit, Pipecat, Claude Agent SDK, Mastra, Vercel AI SDK, or MCP (no-code). Also trigger on direct mentions of "Synap", "Maximem", "maximem-synap", or `synap-*` package names. Covers SDK setup, scoping (User/Customer/Client), ingestion, retrieval, and one drop-in package per framework.