LLM Mart Basic

Use this skill when you need to partition inputs into evidence-backed valid, invalid, and unknown classes based on constraints, rules, and response differences; triggers include 等价类划分 and equivalence partitioning test design.

Use this skill when error taxonomy, retries, timeouts, fallback, or recovery design needs an evidence-bounded review before implementation; triggers include error handling design review, failure-path review, and recovery readiness review.

Use this skill when you need evidence-bounded failover-testing analysis and validation preparation; triggers include 故障切换测试 and failover-testing.

Use this skill when you need to investigate intermittent test failures from run history and evidence; triggers include flaky test analysis.

Use this skill when you need to design functional test plans or cases for business flows, UI, data, and integrations; triggers include functional testing and functional test cases.

Use this skill when you need evidence-bounded repeat inputs, version/model/prompt factors, invariants, variance evidence, and comparison boundaries; triggers include LLM 一致性 and LLM consistency.

Use this skill when you need to design LLM evaluation datasets, judges, metrics, and human-review boundaries; triggers include llm evaluation design.

Use this skill when you need evidence-bounded claim-to-source relations, unsupported assertions, abstention, uncertainty, and evidence review; triggers include LLM 幻觉 and LLM hallucination.

Use this skill when you need to test LLM behavior, failure modes, and evidence-based quality boundaries; triggers include llm testing.

Use this skill when you need to analyze logs into evidence, timelines, anomalies, and follow-up hypotheses; triggers include log analysis.

Use this skill when you need to plan manual or exploratory testing with charters, heuristics, and session records; triggers include manual testing and exploratory testing.

Use this skill when you need to derive test candidates from input transformations and expected relations when a direct oracle is limited; triggers include 变形测试 and metamorphic test design.

Use this skill when you need to identify, contextualize, and investigate metric anomalies from observability evidence; triggers include metrics anomaly analysis.

Use this skill when you need to design mobile test plans for iOS or Android covering functionality, compatibility, performance, network, and security; triggers include mobile testing and app testing.

Use this skill when you need to review mock fidelity, contract alignment, over-mocking, and drift evidence; triggers include Mock 质量评审 and mock quality review.

Use this skill when you need to derive test-path candidates from sourced behavior, state, or process models; triggers include 基于模型的测试 and model-based test design.

Use this skill when you need evidence-bounded delegation, coordination, shared state, conflicts, ownership, termination, and traceability; triggers include 多 Agent 协作 and multi-agent coordination.

Use this skill when you need to interpret mutation operators, killed and survived mutants, and evidence limits; triggers include 变异测试分析 and mutation testing analysis.

Use this skill when you need to discover invalid, denied, failed, degraded, or unsafe-recovery scenarios from product evidence; triggers include negative scenario discovery.

Use this skill when logging, metrics, tracing, alerting, or SLO design needs an evidence-bounded review before implementation; triggers include observability design review, telemetry readiness review, and alert actionability audit.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

A green PR, a controller reporting success, and not one line of the new code running

Quick health check

Find pages that swallowed the graph

Rebuild the index

Import an exported chat history

Ingest book or article highlights

Ingest your own finished work

Ingest newsletters without duplicating

Ingest an academic paper

Ingest a PDF

Clip and ingest a web page

Ingest a voice note

Ingest a video or podcast transcript

Ingest new material from raw/ into the wiki

Scaffold a new vault

Install the skills, commands and agents

What do I know about a topic

Find and add missing connections

Audit structure and repair what is mechanical

Merge two pages

Record a dated metrics snapshot

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.