LLM Mart Basic
@llm-mart · Joined Jun 2026
Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconcil
Partner, channel, and ecosystem marketing for B2B SaaS. Use this skill for co-marketing with technology alliances and channel partners, integration launches, joint campaigns and content, partner tiering and enablement, and cloud-marketplace go-to-market (AWS, Azure, GCP listings,
Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who
Complete B2B SaaS marketing agency powered by 81 AI agents across 17 specialties. This is the entry point for ALL marketing requests. Routes to the right specialist team: content marketing, SEO, paid media, social media, email marketing, design, sales enablement (including techni
End-to-end SEO operations for B2B SaaS organic visibility. Use this skill when you need keyword research, technical SEO audits, content optimization, link building strategy, international expansion, AI/AEO optimization, schema markup, Core Web Vitals improvements, and organic tra
Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free s…
The most expensive bug in AI-assisted building is shipping the wrong thing, well. A CLAUDE.md for PM + eng teams using Claude Code- 7 principles for problem fra…
AI agent skills manager for Claude Code, Cursor, Codex and more — install, sync, and manage skills from one desktop app.
Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis, revenue model identification, market sizing TAM SAM SOM, competitive positioning, bu
Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors
Earnings sentiment analysis, analyst estimates vs guidance, earnings surprise history, consensus sentiment, earnings revision trends, analyst rating changes, earnings beat miss track record, guidance accuracy, whisper numbers, pre-announcement sentiment
Recent quarter performance analysis, quarterly earnings review, last quarter results, quarterly financial performance, analyze recent quarter, Q4 earnings, quarterly revenue breakdown, EPS this quarter, margin analysis recent quarter, sequential growth, quarterly performance revi
Risk analysis, regulatory risk assessment, competitive risk, macro risk, technology risk, litigation risk, financial risk assessment, enterprise risk, operational risk, geopolitical risk exposure
Secular technology trends, technology adoption cycle, disruption risk, AI impact analysis, digital transformation, industry 4.0 trends, technology moat, innovation trajectory, R&D effectiveness, tech competitive positioning
Turnaround analysis, stagnation detection, performance inflection, operational improvement, restructuring analysis, management change impact, cost cutting effectiveness, business transformation, recovery trajectory, operational metrics improvement
Valuation methods analysis, DCF inputs, comparable multiples, P/E ratio, EV/EBITDA, price to book, valuation assumptions, relative valuation, intrinsic value, fair value estimate
Operational KPI tracking, headcount trends, utilization rates, backlog analysis, book-to-bill ratio, operational efficiency metrics, capacity utilization, productivity metrics, operational leverage, same-store sales
Revenue decomposition, segment breakdown, geographic revenue split, product-line waterfall, revenue mix analysis, business segment performance, divisional revenue, revenue concentration, customer revenue dependency, channel revenue analysis
Unit economics analysis, CAC LTV estimation, churn inference, gross margin per unit, customer economics, subscription economics, per-unit profitability, contribution margin, payback period, cohort economics
What-if scenario analysis, scenario tree construction, base bull bear case, sensitivity to macro variables, revenue scenario modeling, cost scenario analysis, margin impact scenarios, interest rate sensitivity, currency impact scenarios, commodity price scenarios
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/explain-issue-fix
Explain issue fix
Explain how tasks in an issue were implemented with detailed breakdown
/find
Find
Search and locate tasks across all orchestrations using various criteria.
/five
Five
Apply the Five Whys root cause analysis technique to systematically investigate issues
/fix-github-issue
Fix github issue
Analyze and fix a GitHub issue with comprehensive testing and verification
/fix-issue
Fix issue
Fix a specific issue or problem with the given identifier or description
/fix-pr
Fix pr
Fetch unresolved comments for current branch's PR and fix them
/future-scenario-generator
Future scenario generator
Generate and analyze future scenarios with plausibility scoring, trend integration, and uncertainty quantification.
/generate-api-documentation
Generate api documentation
Auto-generate API reference documentation
/generate-linear-worklog
Generate linear worklog
You are tasked with generating a technical work log comment for a Linear issue based on recent git commits.
/generate-test-cases
Generate test cases
Generate comprehensive test cases automatically
/generate-tests
Generate tests
Generate comprehensive test suite for $ARGUMENTS following project testing conventions and best practices.
/git-status
Git status
Show detailed git repository status
/hotfix-deploy
Hotfix deploy
Deploy critical hotfixes quickly
/husky
Husky
Verify repository is in working state by running CI checks and fixing issues
/implement-caching-strategy
Implement caching strategy
Design and implement caching solutions
/implement-graphql-api
Implement graphql api
Implement GraphQL API endpoints
/init-project
Init project
Initialize new project with essential structure
/initref
Initref
Build reference documentation by creating markdown files and updating CLAUDE.md
/issue-to-linear-task
Issue to linear task
Convert GitHub issues to Linear tasks
/issue-triage
Issue triage
Triage and prioritize issues effectively
Offline-first Python AI agent that runs a tiny research business: quotes each job against its own costs, collects via Stripe, fulfils with NVIDIA Nemotron, pays…
0 views 0 likesDSH 插件 · 注入式优化器 0.8(主线):你照常说话,它在你发送后,AI接收前把"这一轮到底要什么"理清楚,再把这份理解交给工作 AI(上下文注入) —— 原话不改写,条条带逐字依据。含控制界面(档位/权限/模型/上下文/只读工具)、拦截浮层(思维层+产出层)与真实 token 用量。可明显提升大多数模型的发挥稳…
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