LLM Mart Basic

Condense information with audience-appropriate detail levels.

Write and reason about tests, covering behavior, edge cases, and errors.

Produce clear, structured prose and documentation.

Implements code incrementally with quality gates. Use when the user says 'build' or 'implement', or when starting the implementation phase of an approved plan.

Monitor the CI pipeline for the current branch via a background Monitor script (GitHub or GitLab), reacting to pass, fail, and manual-gate states. Use when the user says 'watch CI', 'monitor the pipeline', 'is CI green', or after pushing a branch or creating a PR/MR.

Runs a structured production-incident investigation that forces evidence-first hypothesis ranking before any code change. Use when given an error message, Sentry alert, failing log, or an 'investigate <X>' request.

Creates or updates a diagram, picking mermaid vs drawio per rules/diagrams.md, writing the source file, and previewing via MCP. Use when the user says 'diagram' or '/diagram', or asks for a flowchart, architecture, sequence, or state diagram.

Drives a fleet of MRs/PRs to done with a manager loop plus the built-in /goal command, delegating all edit, review, rebase, and conflict work to worktree-isolated domain-expert subagents. Use when the user says 'drive fleet' or 'drive the fleet', has 2+ independent lanes to drive

Investigates and fixes a GitHub issue. Use when given an issue number or URL, or when the user says 'fix issue'.

Runs a grilling session that challenges a plan against the existing domain model, sharpens terminology, and updates the CONTEXT.md glossary inline as decisions are made. Use when the user wants to stress-test a plan against their project's language and documented decisions.

Compacts the current conversation into a handoff document another agent can pick up. Use when the user says 'handoff', 'hand off', or wants to continue this work in a fresh session.

Finds deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI

Read and write Jira work items through the acli CLI. Use when the user mentions a Jira ticket, issue, story, bug, or epic, drops a Jira key like SER-123, or pastes an atlassian.net/browse URL.

Create a merge request or pull request from the current branch: verify quality gates, enforce conventional commits, validate the title, and create it without a confirmation step. Use when the user says 'create MR', 'create PR', 'open a merge request', or 'raise a PR'.

Builds a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

Reviews code exclusively for over-engineering and lists what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. Use when the user says 'review for over-engineering', 'is this over-engineered', or invokes /prune. Complements

Starts Phase 1 (Research) for a topic: reads every relevant file, optionally runs a panel of Explore teammates, and saves a research artifact to .claude/state/research/. Use when the user says 'research <topic>' or '/research', or before planning work in unfamiliar code. Research

Reviews a pull request with structured severity-based feedback. Use when asked to review a PR, asked for a code review, or given a PR number/URL.

Fetches and digests Sentry issue data (summary, tags, stack trace, breadcrumbs, latest event) by short ID, numeric issue ID, or sentry.io URL, for any Sentry org the local token can access. Use when the user mentions a Sentry issue or short ID (e.g. MY-PROJECT-4X2), pastes a sent

Runs pre-launch validation and the release workflow. Use when the user says 'ship', 'release', 'deploy', or 'ready to merge'.

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.

`crabbox inspect` prints the full record for a single lease: state, provider,

Run named, repo-local jobs defined in your Crabbox config.

`crabbox list` shows the current Crabbox machines (leases) for a provider. It is

`crabbox login` authenticates the CLI against a coordinator, stores the

`crabbox logout` clears the stored broker token from your user config so the CLI

`crabbox logs` prints the retained command output for a recorded run.

`crabbox marketplace` previews the Crabbox credits gateway: one Crabbox billing

`crabbox media` turns a recorded desktop video into lightweight review

`crabbox open` prepares an existing SSH-capable lease for an external editor.

`crabbox pause` pauses a single lease, freeing the remote compute while

`crabbox pond` is the cross-provider peer-discovery and lifecycle surface for a

`crabbox pool` contains machine-pool helpers. `pool list` keeps the older

`crabbox ports` bridges provider-native port publishing for an existing Crabbox

`crabbox prewarm` leases a reusable box and prepares it for test runs. For

`crabbox providers` prints the provider capability matrix that the CLI compiles

`crabbox receipt <run-id>` retrieves a brokered run's committed terminal

`crabbox results` prints the structured test summary attached to a recorded

`crabbox resume` resumes a lease previously paused with [`pause`](pause.md),

`crabbox run` syncs the current dirty checkout to a box, runs a command there,

`crabbox screenshot` captures a single PNG from a desktop lease without opening a

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