LLM Mart Basic
@llm-mart · Joined Jun 2026
Post-install setup for foundry plugin. Run once after installing on a new machine, or after a plugin version upgrade to sync settings and symlinks. Merges statusLine, permissions.allow, enabledPlugins, and advisorModel into ~/.claude/settings.json; symlinks rules and TEAM_PROTOCO
Prepare release communication and check readiness. Main mode: notes with optional flags --changelog, --summary, --migration, --append (incremental: reruns the full pipeline scoped to newly-landed commits, integrating results into existing DRAFT.md/CHANGELOG.md/SUMMARY.md/MIGRATIO
OSS maintainer fast-close workflow for GitHub PRs. Three phases: (1) PR intelligence — reads full thread, linked issues, PR body to synthesize contribution motivation and classify every comment into action items; (2) conflict resolution — checks out PR branch (fork-aware via gh p
Multi-agent code review of GitHub Pull Requests (Python source, documentation (Markdown/RST), and CI/CD config PRs) covering architecture, tests, performance, docs, lint, security, and API design. TRIGGER when: user provides a GitHub PR number (e.g. 42, #42) and asks to review/au
Post-install setup for the oss plugin. Run once after installing on a new machine, or after a plugin version upgrade, to deliver this plugin's rules/*.md into ~/.claude/rules/ as namespaced symlinks. TRIGGER when: user installed or upgraded the oss plugin and its rules are not lo
Investigation-first debugging — gather evidence, form confirmed root-cause hypothesis, hand off to fix mode with diagnosis file. TRIGGER when: user reports a symptom or failing test with Python traceback, or asks to investigate a runtime/CI failure with reproducible evidence; phr
TDD-first feature development — crystallise API as a demo test, drive implementation to pass it, run quality stack and progressive review loop. TRIGGER when: user asks to build new functionality, add a capability, or implement a feature in a Python project; phrases: "add X", "imp
Reproduce-first bug resolution — capture bug in failing regression test, apply minimal fix, run quality stack and review loop. TRIGGER when: user reports a bug, regression, or unexpected behaviour in Python code with a traceback, failing test, or issue number; phrases: "fix this
Analysis-only planning — classify and scope a task without writing code; outputs a structured plan to .plans/active/. TRIGGER when: user wants to understand scope and risks before implementation; phrases: "plan this", "scope out X", "what would it take to Y", "analyse before we s
Test-first refactoring — audit coverage, add characterization tests, apply changes with safety net, run quality stack and review loop. TRIGGER when: user wants to restructure existing Python code without changing behaviour; phrases: "refactor X", "clean up Y", "extract Z", "restr
Multi-agent code review of local Python files, directories, or the current git diff covering architecture, tests, performance, docs, lint, security, and API design. Scope: Python source files in local working tree. Python-file-free targets (pure JS/TS/Go/Rust projects) are out of
Post-install setup for the develop plugin. Run once after installing on a new machine, or after a plugin version upgrade, to deliver this plugin's rules/*.md into ~/.claude/rules/ as namespaced symlinks. TRIGGER when: user installed or upgraded the develop plugin and its rules ar
Systematic ablation study runner. After research:run finds improvements, fortify identifies component candidates from git diff + diary, creates isolated git worktrees per ablation (main repo never modified), runs metric+guard in each worktree, ranks component importance, and opti
Research-supervisor review of program.md — validates experimental methodology (hypothesis clarity, measurement validity, control adequacy, scope, strategy fit), emits APPROVED / NEEDS-REVISION / BLOCKED verdict before expensive run loop.
Generate a Kaggle competition notebook as a Jupytext `# %%` Python script following the user's established ML research style: PTL for DNN training, best-fit tool selection, EDA→Baseline→Train→Inference pipeline with per-stage lens cells, small single-purpose cells each carrying a
Interactive wizard that scans the codebase, proposes a metric/guard/agent config, and writes a program.md run spec. Also runs cProfile on a file path to surface bottlenecks before prompting for optimization goal.
Post-run retrospective: reads .experiments/ JSONL, computes Wilcoxon significance, detects dead iterations, flags suspicious jumps, generates next-hypothesis queue for --hypothesis flag.
Sustained metric-improvement loop with atomic commits, auto-rollback, and experiment logging. Iterates with specialist agents, commits atomically, auto-rolls back on regression. Accepts a program.md file path. Supports --resume, --team, --colab, --codex, --researcher, --architect
Post-install setup for the research plugin. Run once after installing on a new machine, or after a plugin version upgrade, to deliver this plugin's rules/*.md into ~/.claude/rules/ as namespaced symlinks. TRIGGER when: user installed or upgraded the research plugin and its rules
Non-interactive end-to-end pipeline — auto-configure program.md (accept defaults), run judge+refine loop (up to 3 iterations), then run the campaign. Single command from goal to result.
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.
/vet
Vet
Vet the staged change: run the implement-review review loop (short alias)
/learn
Learn
Extract a learning from the recent conversation and add it to the appropriate instruction file
/learn
Learn
Extract a learning from the recent conversation and add it to the appropriate instruction file
/create-pipeline
create-pipeline
Create a new pipeline from a task description. Fans out agent, skill, and hook scaffolding in parallel, then integrates into the routing system.
/d
D
Jev-first router: A/B variant of /do. One TypeSafe call replaces the manifest read; falls back to /do when unavailable or unconfident.
/do
Do
Smart router: classify requests and route to the correct agent + skill
/generate-claudemd
Generate claudemd
Generate project-specific CLAUDE.md from repo analysis.
/github-notifications
Github notifications
Triage GitHub notifications: fetch, classify, report actions needed.
/github-profile-rules
Github profile rules
`github-profile-rules` — extract programming rules and coding conventions from a GitHub user's public profile via API.
/gm-brilliant-implementation
Gm brilliant implementation
Run the complete 34-stage implementation workflow for a large, multi-system, multi-wave, or CPU-delegated 5 Star Booker GM program.
/install
Install
Plan, then apply, the VexJoy Agent install with the vexinstall engine
/pr-review
Pr review
Comprehensive PR review using specialized agents, with automatic retro knowledge capture
/reddit-moderate
Reddit moderate
Reddit moderation: fetch modqueue, classify content, take mod actions
/retro
Retro
Learning system interface: stats, search, graduate learnings. Backed by learning.db (SQLite + FTS5).
/system-upgrade
system-upgrade
Systematic upgrade pipeline for adapting agents, skills, and hooks when Claude Code ships updates, user goals change, or retro learnings accumulate.
/full-equity-research
Full equity research
agentii.full-equity-research — the spec 046 kit command. Use the Skill tool to run agentii:full-equity-research on this workspace.
/synthesize
Synthesize
agentii.synthesize — the spec 046 kit command. Use the Skill tool to run agentii:synthesize on this workspace.
/agent-diversity-review
Agent diversity review
Run the Agent Diversity Review gate and emit the result table
/create-specialist-agent
Create specialist agent
Scaffold a new spawnable specialist agent def and register it in the agent taxonomy
/customer-changelog-check
Customer changelog check
Audit whether user-visible changes in the current session have matching CHANGELOG.md entries; report MISSING with suggested lines; --fix auto-appends
Persistent session memory for AI coding agents — local-first, with on-device inference, associative recall, and drift detection. Works with Claude Code, Cursor,…
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