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.

Check frontmatter against the schema

Pull knowledge into a project

Scan for credentials

Show what a claim rests on

Split an overloaded page

Find concept pages nobody has touched

Audit the tag vocabulary

How my sources developed over time

Show which pages an answer used

Add relation types where they matter

The weekly review

Implement an approved plan or issue in its own worktree, run the gate, open the pull request.

Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.

Write the repository handoff file for the next session, and record any durable learning.

Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.

Turn a topic or issue into a plan the reviewer approves in the native plan pane.

Answer a research question with parallel read-only gatherers and one synthesized digest.

Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.

Transform a vague prompt into precise, structured AI instructions

Implement an approved plan or issue in its own worktree, run the gate, open the pull request.

Open-source, self-hosted AI media server. One server replaces your entire media stack, with a web app, native iPhone app, and an AI agent that gets things done.…

A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.

🦦 Crayotter: A Multimodal AI-Agent for Video-Editing, Video-Composing, and Video Production. Powered by Multimodal LLMs for autonomous Text-to-Video agentic fr…

Webextension tool for Odoo