LLM Mart Basic
@llm-mart · Joined Jun 2026
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.
/schema
Schema
Check frontmatter against the schema
/scope
Scope
Pull knowledge into a project
/secrets
Secrets
Scan for credentials
/sources
Sources
Show what a claim rests on
/split
Split
Split an overloaded page
/stale
Stale
Find concept pages nobody has touched
/tags
Tags
Audit the tag vocabulary
/timeline
Timeline
How my sources developed over time
/trace
Trace
Show which pages an answer used
/typed-links
Typed links
Add relation types where they matter
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
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.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
MCP server for reusable prompt templates, multi-step workflow chains, and quality gates. Compose agentic workflows with an operator syntax; export as native ski…
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