LLM Mart Basic

Connect Cargo to an external system and find out what it can do — authenticate connectors, browse the integration catalog, and resolve the `connectorUuid` and `actionSlug` a workflow node needs. Triggers: "connect my HubSpot", "is Salesforce connected", "what integrations do you

Manage the knowledge a Cargo workspace holds — upload files (PDF, CSV, text), rename and organize them, and build native or connector-backed libraries that sync from an external source, so agents can retrieve them (RAG). Triggers: "upload this PDF", "add these docs as knowledge",

Read and write the workspace GTM knowledge base — the git-backed repository of markdown describing ICPs, personas, plays, proof points, objections, competitors, and signals — plus its runtime sandbox and typed knowledge graph. Triggers: "document our ICP", "write up this persona"

Explain what a Cargo run or batch actually did, after the fact — trace one run node by node, draw the graph it executed with the failing step marked, sweep a batch or play for errors grouped by root cause, and attribute credit spend down to the node and the provider. Triggers: "w

Do business-to-business go-to-market work on Cargo — research accounts and buying committees, enrich and verify B2B contact records from licensed data providers, score and qualify leads, draft permission-based outreach for the user's own sequencer, sync to CRM, and monitor buying

Send mail from inboxes Cargo owns — provision mailboxes on a sending domain, run provider warm-up and the 5→40/day send ramp, deliver with the `sendEmail` action, and read back threads, replies, delivery events, and the workspace suppression list. Triggers: "set up a sending mail

Watch a Cargo workspace and get told when something breaks — scheduled threshold alerts over workflow telemetry (spans, runs, records), a storage model freshness or row count, or any SQL query, firing a connector, tool, or agent when a metric breaches. Triggers: "alert me when",

Make Cargo actually run something, or show what it would run — execute one connector action, run a multi-step workflow, trigger a batch across a whole segment or model, message an AI agent, build or edit a node graph, draw a workflow, tool or play as a diagram, and query the runt

Guided first-run demo for Cargo — one persona question to 25 real leads with a cost receipt in under two minutes, ending by saving the pull as a recurring play. Triggers: "show me what Cargo can do", "give me a demo", "take me on a tour", "quickstart", "getting started with Cargo

Define and use segments — named, saved filters over a Cargo model that become the audience for a batch run, a play trigger, or an export. Triggers: "build a segment of", "filter my contacts where", "who matches this criteria", "save this as a list", "how many companies match", "t

Work with the data inside a Cargo workspace — models (Companies, Contacts, Deals…), datasets, columns, relationships, records, and SQL over workspace storage. Triggers: "what models do I have", "show me the schema", "add a column for", "how many contacts do I have", "SELECT … FRO

Administer a Cargo workspace and talk back to the Cargo team — invite and manage members, mint and rotate API tokens, organize plays, tools, and agents into folders, inspect roles, upload batch input files, and file reports. Triggers: "invite my teammate", "create an API token fo

Compose a Cargo GTM execution plan — stage-by-stage provider + action slugs with per-step credit costs, a sample as the first step (1–3 rows for a single action, 10–20 records before any batch), and budget reconciliation against the live balance. Use before any multi-stage GTM ru

Execute one bounded, pre-approved slice of a Cargo sourcing job (a single search/lookup action with a fixed row cap and credit budget) and return raw structured rows to a file. Spawn several in parallel to sweep a wide criteria space (per-industry, per-geo, per-title). Only use A

Imported from getcargohq/cargo-skills/cargo-gtm/agents/execution-plan-creator.md.

Imported from getcargohq/cargo-skills/cargo-gtm/agents/list-builder.md.

Final acceptance orchestrator for contract-oriented workflows

Verify each Cell's CODEMANIFEST against the implementation

Generate the final acceptance report with verdict

Defines the acceptance scope — the set of cells for a given functionality

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.

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.

Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.

Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Execute tasks from a track's implementation plan following TDD workflow

Manage track lifecycle: archive, restore, delete, rename, and cleanup

Create a new track with specification and phased implementation plan

Git-aware undo by logical work unit (track, phase, or task)

Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)

Display project status, active tracks, and next actions

Restore saved project context and decisions to resume a session

Save project context, decisions, and progress for a later session

Build features guided by data insights, A/B testing, and continuous measurement

Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring

Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring

Migration monitoring, CDC, and observability infrastructure

SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…