LLM Mart Basic

Suede-owned artist campaign rollout. Use when an artist, song, release, era, show, or catalog moment needs a complete campaign across surfaces: hooks, rituals, visuals, merch, rollout calendar, email, site copy, fan actions, setlists, and collaborator outreach. NOT FOR: single-su

Suede-owned retention discipline for voluntary and involuntary churn: cancel flows, pause paths, evidence-based save offers, failed-payment recovery, proactive signals, and win-back design. Use when diagnosing subscriber loss or designing a bounded retention intervention. NOT FOR

Suede Labs AI CI and branch-protection wiring for any repo and any stack: path-aware jobs, a single aggregator required check that cannot deadlock, lockfile hygiene, runtime pinning from the repo, and the exact branch-protection settings. Use when asked to set up CI, protect main

Suede-owned short-to-long content funnel blueprint. Use when turning a video, clip, interview moment, talk excerpt, screen recording, or transcript into a repeatable package that bridges attention to an X Article, LinkedIn article, newsletter, blog guide, or playbook, or when thi

Suede-owned co-marketing discipline for partner fit, audience overlap, joint offers, shared distribution, operating roles, measurement, and fair credit. Use when identifying potential partners or planning a specific joint campaign or cross-promotion. NOT FOR: affiliate or custome

Suede Labs AI combined code review and ship grade in one pass: findings with file:line evidence plus an A-F lane grade, Instant-F security triggers, OWASP checks, a deploy-safety gate, and fix briefs. Use when asked to review this, grade this, security-check this, is this safe to

Suede Labs AI blunt A-F ship grade for a code change across correctness, security and permissions, data and state, domain truth, UX and release behavior, tests and verification, and deploy readiness, with Instant-F triggers and evidence-based grade caps on auth, payment, migratio

Suede Labs AI findings-only code review with full context: changed files, callers, contracts, and deploy surface. Covers TypeScript, React, Next.js, database, Swift/iOS, OWASP, accessibility, SEO, observability, commit hygiene, and deploy risk, ranked P0-P3 with file:line evidenc

Suede-owned B2B cold-email discipline for evidence-based personalization, subject lines, opening lines, concise bodies, one clear CTA, and bounded follow-up sequences. Use when writing or repairing outbound email to qualified prospects. NOT FOR: building or qualifying the prospec

Suede-owned community-growth discipline for member purpose, platform choice, seeding, rituals, moderation, health metrics, and earned advocacy. Use when starting, auditing, or growing a Discord, Slack, forum, subreddit, or comparable product community. NOT FOR: public social-chan

Suede-owned competitive-intelligence discipline for evidence-backed profiles of positioning, pricing, messaging, product, proof, and public-market signals. Use when researching named competitors from current public URLs or refreshing a structured landscape. NOT FOR: publishing co

Suede-owned comparison-page discipline for honest alternative, versus, and competitor-comparison content that serves evaluators and search intent. Use when planning or writing a public page that positions products against named alternatives from verified evidence. NOT FOR: gather

Suede-owned content-strategy discipline for audience questions, content pillars, topic clusters, editorial priorities, cadence, distribution, refreshes, and stop-doing decisions. Use when deciding what to publish, why it deserves resources, and how the portfolio compounds. NOT FO

Suede Labs conversion-copy writer: landing sections, email, microcopy, buttons, headlines, CTAs, variants, and anti-slop edits. Use when asked to write or rewrite conversion copy for one surface in one pass — a hero, a button set, an email subject, a README section, a product blu

Suede-owned customer-research discipline for interview design, transcript and ticket synthesis, review and forum mining, quote banks, jobs, and evidence-backed personas. Use when discovering or synthesizing what a defined customer segment actually says, does, needs, and resists.

Suede Labs AI design skill for making an interface feel intentional instead of templated: design tokens, color strategy, OKLCH ramps, type scale, fluid type, visual hierarchy, dark mode, spacing, component laws, motion, and source-to-implementation visual QA. Use when asked to de

Suede Labs anti-slop pass: strip AI writing patterns from prose before anything goes public. Em dashes, filler openers, manufactured enthusiasm, false agency, passive voice, formulaic structures, all of it. Use when copy, a README, an email, a social post, or a doc is about to sh

Suede-affiliated directory distribution strategy for selecting listings, sequencing submissions, tailoring positioning, and verifying backlinks. Use when a product needs startup, SaaS, AI, MCP, marketplace, or review-directory submissions and a measurable tracker. NOT FOR: broade

Suede-owned lifecycle email design for welcome, onboarding, nurture, re-engagement, post-purchase, and trigger-based sequences. Use when the user needs a multi-email flow with entry criteria, cadence, message roles, and a measurement plan — drip campaigns, welcome series, win-bac

Suede-affiliated engineering-as-marketing strategy for selecting, scoring, and scoping calculators, graders, generators, and other free interactive tools. Use when the user wants a lead, link, education, or product-adoption asset with a measurable path to the paid product. NOT FO

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.

Daily standup: all 8 departments report on the current project in parallel

Identify skills injected where not needed, propose regex and description tightening

Draft X/Twitter announcement post (or thread) for the latest plugin release

Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste

Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes

Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization

Propose a skill revision and compare fresh executions under a frozen rubric

Prune stale entries from the whetstone sync decision log

Bump version, commit, push, mirror to ai-skills, and update local plugin

Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).

Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns

Triage all open PRs with parallel agents, label, group, and review one-by-one

Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).

Create Architecture Decision Records with format selection and lifecycle management

Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps

Explore requirements and approaches through collaborative dialogue before planning implementation

Create engaging changelogs for recent merges to main branch

Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps

Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.

Record a video walkthrough of a feature and add it to the PR description

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.