LLM Mart Basic

Use when turning one named customer's measured win into a case study, or the attributed testimonial quote that travels with it — consent-cleared, metrics-anchored proof for the next skeptical buyer. NOT the deck that sells the vision to a room (that is `pitch-deck`), NOT thought-

Use when building or shipping a Manifest V3 browser extension and hitting its quirks — service worker dying and losing state, permission warnings, a Chrome Web Store rejection, content-script/worker/popup messaging, or an MV2-to-V3 migration. NOT a generic web app (that is `nextj

Use when a spec exists and must be de-risked before planning — hunt its ambiguities, unstated assumptions and edge cases, ask the few build-changing questions, bake the answers back into the spec. The rsc SDD gate between `specify` (writes the spec) and `plan` (designs the build)

Use when running a ClickHouse server for high-volume OLAP: choosing a MergeTree engine and ORDER BY/PARTITION BY keys, ingesting billions of event/log/metric rows, pre-aggregating with materialized views, or fixing a query that scans instead of pruning. NOT in-process file analyt

Use when a deal closed or a user signed up and the first 30 days need an activation plan: sales→delivery handoff, one verifiable activation event, kickoff, and a 30/60/90 or day-0→14 plan with owners, dates and a measurable exit. NOT reactive ticket triage (that is `customer-supp

Use when working on Cloudflare's edge platform — wrangler.jsonc bindings, choosing between D1/KV/R2/Durable Objects/Queues, deploying a Worker or SPA via Static Assets, or designing around a Workers runtime limit. NOT generic CI/release (that is `deployment`), NOT Next.js framewo

Use to judge a concrete diff, branch, or GitHub PR on its own merits with no rsc-SDD spec/plan chain to key off — the spec-less giving pass behind /code-review: only findings you can defend, one verdict, read-only unless --comment or --fix. NOT the SDD gate keyed to 02-DOCS/wiki/

Use when you land in an unfamiliar or inherited codebase and must get productive fast: a breadth-first map of entry points, request flow, module ownership, hidden side effects (cron, webhooks, workers) and churn hotspots, committed as CODEBASE-MAP.md. NOT a deep audit of one modu

Use when writing a cold email or LinkedIn DM to a stranger and its cadence: first-touch copy under a word ceiling, 4-7 step bump sequences, per-inbox volume and warm-up limits, the compliant opt-out footer. NOT SPF/DKIM/DMARC setup (that is email-deliverability), NOT sourcing the

Use when building or running a persistent two-way community space — Discord, Telegram, Circle: platform choice, structure, onboarding, native→bot→human moderation, rituals, growth loops, health metrics. NOT churn of paying product customers (that is `retention`), NOT broadcast em

Use when an already-named set of rivals is watched on a cadence — pricing, features, positioning and changelog diffed into a maintained tracker plus an append-only, classified change log. NOT sizing the market or choosing who the rivals are (that is `market-research`), NOT one-of

Use when scoping which regulatory frameworks bind a business — SOC 2, ISO 27001, HIPAA, PCI DSS, EU AI Act, DORA, NIS2 — building a control register with owners and evidence, or standing up the cadence that keeps it audit-ready. NOT drafting privacy-policy/ROPA/DPA or ToS text (t

Use when building one shared Compose UI in Kotlin across Android, iOS, and desktop — commonMain @Composables, expect/actual, source-set placement, native interop, multiplatform ViewModel/navigation/Koin. NOT a single-platform native build (that is kotlin-android / swift-ios), and

Use when setting or amending a project's non-negotiables — stack canon, quality bars, conventions, security/a11y floors — as numbered, testable rules later phases obey. First rsc-sdd phase; writes 02-DOCS/wiki/sdd/constitution.md. NOT a feature spec (that is `specify`), NOT the t

Use when a content operation needs a SYSTEM: a dated editorial calendar built top-down from pillars, plus the stage gates, briefs, WIP limits and 1:10 atomization plan that move each slot to publish-ready. NOT writing the pieces (that is `article-writing`), NOT publishing them (t

Use when drafting or reviewing business contracts and clauses in plain language — NDAs, MSAs, SOWs, contractor agreements, risk boilerplate (liability caps, indemnity, force majeure, termination, IP) — or redlining a counterparty's paper. NOT consumer Terms of Service (that is te

Use when self-hosting apps and databases with Coolify on a VPS you own — install, first-admin lockdown, Git-to-deploy (Nixpacks/Dockerfile/compose), managed Postgres/Redis, scheduled S3 backups, domains + auto-SSL. NOT a PaaS someone else runs (that is `railway`), NOT sizing/hard

Use when metering and capping AI or cloud app spend — tokens read from the response `usage` object, priced off a dated rate table, ledgered per user/tenant/feature, with alerts and a hard cap before the bill. NOT cash runway (that is `finance-ops`), NOT cost-per-unit margin (that

Use when turning "I want to teach X" into a defensible course skeleton — measurable outcomes (Bloom + ABCD), assessment that proves each one, sequenced modules, and an outcome×module×assessment matrix — for a workshop, bootcamp, cohort or onboarding track. NOT making one concept

Use when lesson or course content is correct but forgettable and a concept has to LAND: profiles the learner, breaks the blocking false belief, then rebuilds it as epiphany story → named model → grounded analogy → proof → so-what. NOT outcomes, assessment or module order (that is

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

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.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

MCP server for reusable prompt templates, multi-step workflow chains, and quality gates. Compose agentic workflows with an operator syntax; export as native ski…

中国股票数据基础设施，覆盖行情、研报、资金面、筹码、公告、龙虎榜、ETF/期权、舆情互动、基本面、行业板块、宏观与风险事件等核心数据。42+A股数据集，日更、自托管、MCP 原生，零注册、零 API Token

OKF (Open Knowledge Format): Durable, structured memory for AI agents. Author, validate, consume, and maintain portable knowledge bundles through an ecosystem o…

토스증권을 AI 에이전트와 터미널에서 다루는 도구. CLI 와 MCP 서버로 계좌·시세·주문은 물론 웹앱 전용 기능(수급·AI 시그널·스크리너·배당)까지, JSON·CSV 구조화 출력으로 AI 도구·자동화에 바로 연동.

Claude skills for LinkedIn. 11 Claude Code and Codex skills that write human-sounding LinkedIn posts, craft comments that get noticed, analyze your feed, and bu…

MCP server connecting AI agents to ITASCA engines (PFC, FLAC, 3DEC, MPoint, MassFlow) — run geotechnical & geomechanics simulations through natural conversation

A curated list of amazingly awesome articles, people, applications, software libraries and projects related to the knowledge management space

One local dashboard for every Claude Code, Codex, Cursor, Antigravity, and Kilo Code session on your Mac. Spawn in parallel, ship in parallel. Open source, MIT.

Building blocks for frontier OpenAI agents in Rust. Nanocodex empowers you with Codex-level performance anywhere.

The AI agent that lives in your framework/browser

Self-Programming AI Assistant. Capture, automate, and refine all your workflows.

Consider it done. The open-source AI agent that works out of the box · 想到，就能做到。开源、开箱即用的 AI Agent。

Make Any Website into CLI & Use your logged-in browser by AI agent.

ISO 24495 Plain Language skills and Claude Code plugin

Deterministic, fail-open tool routing for Hermes Agent with an optional local-model fallback.

1인 사업가 생산성 키트 — 직원 없이 49개를 자동화했고, 그중 바로 쓸 수 있는 AI 에이전트 스킬 26개(+실행 스크립트)를 공개합니다

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agent…

The open-source, self-hosted video conferencing software. Scalable, customizable, and with a powerful AI Meeting Agent.

Business operating system for Claude Code — 57 skills, 21 agents, smart daemon. Unified inbox (WhatsApp/Email/Slack/Telegram), autonomous PR merge, full-AWS mon…

A local-first, cross-platform Electron desktop workspace for Pi Coding Agent, with sessions, project files, browser tools, skills, plugins, and messaging integr…