AI & ML

dvy1987 Bundle

Design state-of-the-art multi-agent systems, orchestration patterns, and wiring from scratch. Load when the user asks to build an agent system from scratch, design agent orchestration patterns, choose between sequential/parallel/hierarchical workflows, or define how multiple agents should collaborate. Also triggers on "agent architecture", "multi-agent wiring", "agent orchestration pattern", "how to connect these agents", "design the communication structure". Called by agent-builder for complex topologies (>4 agents or hierarchical). For process-driven agent design, use agent-builder instead.

dvy1987 Bundle

Bootstrap full agent infrastructure for an existing, already-coded project without modifying a single line of source code. Surveys the repo, infers conventions from manifests, README, git history, and source samples, then generates the missing AGENTS.md, docs/architecture.md, docs/product-soul.md, ADR backfill, and seeded docs/memory/ files. Asks the user only about gaps the repo cannot reveal. Load when the user asks to "retroactive project setup", "backfill agent infrastructure", "bootstrap agents for this existing repo", "onboard agents to a legacy codebase", "set up agents without touching code", or "fill in missing agent context for this project".

dvy1987 Bundle

Capture the "why" behind technical choices to prevent architectural drift. Load when the user makes a major technical decision, chooses a library/framework, defines a system boundary, or changes a core architectural pattern. Also triggers on "record a decision", "write an ADR", "why did we do this", "document this architectural choice", or "architectural decision record". Supports `SYNTHESIS=true` mode for retrospective ADR backfill from observed repo state — used by `retroactive-project-setup` and any future backfill skill. Essential for long-term project maintainability and agent alignment.

dvy1987 Bundle

Security checks for repository ingestion — scans repos for poisoned examples, dependency and supply-chain attacks, file/path traversal, format-based attacks, and enforces quarantine-before-commit. Load as part of the secure-* skill sequence whenever an agent reads, ingests, or learns from a GitHub repository. Also load when the user asks to check a repo for poisoned code, scan dependencies, verify supply chain safety, check for path traversal, scan repo files for attacks, or audit a repo before ingestion. Covers Issues 3, 4, 7, 8 from the agent security threat model: poisoned training data, dependency attacks, file/path attacks, and format-based attacks.

promisingcoder Skill

Use when reviewing, reproducing, or proving MarketingClaw Telegram behavior with a real Telegram user on Crabbox, including PR review workflows that need an agent-controlled Telegram Desktop recording, TDLib user-driver commands, Convex-leased credentials, WebVNC observation, and motion-trimmed artifacts.

ssrjkk Bundle

Fine-tunes open-source LLMs (Llama, Mistral, Qwen) using LoRA/QLoRA with HuggingFace and Unsloth. Use for domain-specific model adaptation.

ssrjkk Bundle

Designs and curates few-shot examples to guide LLM behavior, including example selection, formatting, and ordering. Use for task specification without fine-tuning.

ssrjkk Bundle

LLM observability with Langfuse/LangSmith

claude-dev-suite Skill

Security review of AI-generated code, and secure practices for working with coding assistants. USE WHEN: reviewing AI-generated code (GitHub Copilot, ChatGPT, Claude, etc.) for security vulnerabilities, or establishing secure AI coding practices DO NOT USE FOR: AI/ML model security, prompt injection attacks on AI systems, or general code review

byte886 Bundle

将一条已经成功跑通的真实任务，从聊天记录、执行日志、输入输出文件和用户反馈中提炼为可复用 Skill。用于用户说“把刚才的流程沉淀成 Skill”“把这次成功经验固化下来”“以后重复做这类任务”“从运行记录生成 SKILL.md”时；也用于判断当前经验更适合保存为 Prompt、SOP、模板还是 Skill。不要用于尚未跑通、没有可验证结果，或用户只是想执行原始业务任务的场景。

byte886 Bundle

审查现有 Agent 工位拆分、连接、交接、退回与人工边界。适用于用户已有岗位卡、工作流、上下游判断、接力协议或失败记录时，先判断哪些工作更适合 Tool、Skill、固定 Workflow、Agent 或 Human，再检查是否值得连接、怎样验收、出错退给谁；不预设 Agent 数量。

tae2089 Skill

code-context-graph — documentation generation, RAG indexing, and docs quality linting.

ethan-paseya Bundle

Amazon review and VOC analysis using SellerSprite MCP. Use when the user runs `/review-analysis {ASIN} {SITE}` to analyze positive and negative reviews, identify product pain points, listing mismatch, service risks, and product improvement actions.

ethan-paseya Bundle

Amazon keyword library research using SellerSprite MCP. Use when the user runs `/keyword-research {ASIN} {SITE}` to collect keyword data, classify terms into eight dimensions, and produce advertising and listing keyword strategy outputs.

ethan-paseya Bundle

Amazon product opportunity research using SellerSprite MCP and LLM reasoning. Use when the user runs `/product-research "{PRODUCT_KEYWORD}" {SITE}` to research a product direction, evaluate market opportunity, competitors, VOC, barriers, and launch decision.

ethan-paseya Bundle

Amazon review and VOC analysis using SellerSprite MCP. Use when the user runs `/review-analysis {ASIN} {SITE}` to analyze positive and negative reviews, identify product pain points, listing mismatch, service risks, and product improvement actions.

ethan-paseya Bundle

Amazon keyword library research using SellerSprite MCP. Use when the user runs `/keyword-research {ASIN} {SITE}` to collect keyword data, classify terms into eight dimensions, and produce advertising and listing keyword strategy outputs.

ethan-paseya Bundle

Amazon product opportunity research using SellerSprite MCP and LLM reasoning. Use when the user runs `/product-research "{PRODUCT_KEYWORD}" {SITE}` to research a product direction, evaluate market opportunity, competitors, VOC, barriers, and launch decision.

hatayama Skill

Returns a simple 'Hello World' message. Use this tool for testing MCP connection.

archibate Bundle

Create or edit agent-facing/LLM prompts using modern prompt-engineering practices. Use this skill before editing agent-facing docs, rule files, references, skills, memory, or any form of LLM prompt. Also use it before writing LLM tests or evaluations. This is mandatory: NEVER skip this skill before writing agent-facing text; MUST use it before editing a file that will be fed to AI agents.

rafadgarcia Bundle

Prisma Client API reference covering model queries, filters, operators, and client methods. Use when writing database queries, using CRUD operations, filtering data, or configuring Prisma Client. Triggers on "prisma query", "findMany", "create", "update", "delete", "$transaction".

nathanonn Bundle

Convert a Node.js CLI tool specification (even a vague one) into a Codex /goal-ready bundle — GOAL.md, VERIFY.md, PROGRESS.md inside goals/<slug>/ — with AI-agent-friendly patterns (--json, stdout/stderr separation, exit codes, structured errors, TTY detection, --dry-run) baked into every goal. Asks clarifying questions in focused batches (each with options + recommendation + reasoning), reaches 95% confidence, optionally scaffolds a missing CLI project (bin/, src/, package.json, AGENTS.md, CLAUDE.md behavioral snippet), and emits a tailored /goal command. Handles both new CLIs and adding commands to existing ones. Supports JavaScript (default) and TypeScript, commander.js, Vitest, conditional SQLite and cosmiconfig. For Node.js CLI tools, not web apps, servers, or non-Node projects.

cyanheads Skill

Scaffold a new MCP tool definition. Use when the user asks to add a tool, create a new tool, or implement a new capability for the server.

cyanheads Skill

Reference for core and server configuration in `@cyanheads/mcp-ts-core`. Covers env var tables with defaults, priority order, server-specific Zod schema pattern, and Workers lazy-parsing requirement.

cyanheads Skill

Canonical reference for the unified `Context` object passed to every tool and resource handler in `@cyanheads/mcp-ts-core`. Covers the full interface, its `RequestContext` base, all sub-APIs (`ctx.log`, `ctx.state`, `ctx.requestInput`, `ctx.inputs`, `ctx.enrich`, `ctx.content`), and when to use each.

cyanheads Skill

Testing patterns for MCP tool/resource handlers using `createMockContext` and Vitest. Covers mock context options, handler testing, McpError assertions, format testing, Vitest config setup, and test isolation conventions.

cyanheads Skill

Investigate, adopt, and verify dependency updates — with special handling for `@cyanheads/mcp-ts-core`. Captures what changed, understands why, cross-references against the codebase, adopts framework improvements, syncs project skills, and runs final checks. Supports two entry modes: run the full flow end-to-end, or review updates you already applied.

cyanheads Skill

Catalog of OpenTelemetry instrumentation built into framework `@cyanheads/mcp-ts-core` — spans, metrics, completion logs, env config, runtime caveats, custom instrumentation patterns, and cardinality rules. Use when enabling OTel export, adding custom spans or metrics in services, debugging missing telemetry, looking up attribute names, or deciding what's safe to put on a metric attribute vs. a span.

cyanheads Skill

Code review and cleanup against a working tree of changes, or against a named path or whole codebase. Analyzes `git diff` (or the named target) to simplify, consolidate, and align code with the existing codebase — modernize syntax, remove unnecessary complexity, consolidate duplicated logic, catch efficiency issues. Use after a substantive working session, or when asked to clean up, simplify, reduce slop, consolidate, modernize, tighten up, de-slop, or scan a codebase. For `@cyanheads/mcp-ts-core` projects, includes specific transformations for tool/resource/prompt definitions, the ctx pattern, error factories, and framework idioms.

cyanheads Bundle

Finalize documentation and project metadata for a ship-ready MCP server. Use after implementation is complete, tests pass, and devcheck is clean. Safe to run at any stage — each step checks current state and only acts on what still needs work.

cyanheads Skill

Design the tool surface, resources, and service layer for a new MCP server. Use when starting a new server, planning a major feature expansion, or when the user describes a domain/API they want to expose via MCP. Produces a design doc at docs/design.md that drives implementation.

cyanheads Skill

File a bug or feature request against this MCP server's own repo. Use for server-specific issues — tool logic, service integrations, config problems, or domain bugs that aren't caused by the framework.

cyanheads Skill

Ship a release end-to-end across every registry the project targets (npm, MCP Registry, GitHub Releases for `.mcpb` bundles, GHCR). Runs the final verification gate, fast-forwards `main` when the release rode a release PR, creates the annotated tag on the commit `main` now points at, pushes commits and tags, then publishes to each applicable destination. Assumes git wrapup (version bumps, changelog, commit stack — and in release PR mode, the pushed branch and open PR) is already complete — this skill is the post-wrapup merge + tag + publish workflow. Retries transient network failures on publish steps; halts with a partial-state report when retries are exhausted or the failure is terminal.

cyanheads Skill

File a bug or feature request against @cyanheads/mcp-ts-core when you hit a framework issue. Use when a builder, utility, context method, or config behaves contrary to the documented API — not for server-specific application bugs.

dvy1987 Bundle

Author the project's non-negotiable engineering rules — the constitution that every feature spec, plan, and implementation must satisfy. Load when the user asks to write a constitution, define project rules, set engineering invariants, write project standards, define non-negotiables, capture agent guardrails as policy, or when spec-driven-development orchestrator routes here. Also triggers on "project constitution", "engineering invariants", "non-negotiable rules", "project policy", "set our standards", "/constitution". Output: docs/constitution.md. The third strategic artifact alongside AGENTS.md (agent behavior) and product-soul (strategy).

dvy1987 Bundle

Route user requests to the right skill, decompose complex work into parallel subagents, and manage project phase transitions. Load when the user asks "what should I do next", "which skill should I use", "orchestrate this", "run the full workflow", "split this into parallel tasks", or when a complex request spans multiple skills. Also triggers on "coordinate agents", "parallel execution", "task decomposition", "agent workflow", "what phase am I in", or when the user gives a broad instruction that requires multiple skills in sequence. This is the project's brain — it decides what runs, when, and whether to parallelise.