LLM Mart Basic
@llm-mart · Joined Jun 2026
Uses MCP Connectors to read Gmail inbound leads, score them by ICP fit, draft personalized responses, and log qualified leads to your CRM. Turns your inbox into an automated pipeline.
Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.
Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.
Design docs that reduce cognitive load. Trigger: writing guides, READMEs, RFCs, onboarding, architecture, or review-facing docs.
Write warm, direct collaboration comments. Trigger: PR feedback, issue replies, reviews, Slack messages, or GitHub comments.
Use Gentle AI harness discipline for Pi work: clarify first, preserve OpenSpec artifacts, use strict TDD where available, delegate through subagents when useful, and protect review workload.
Create and triage GitHub issues from repository evidence. Trigger: issue creation, bug reports, feature requests, or issue approval.
Trigger: judgment day, judgement day, dual review, adversarial review, juzgar. Run explicit blind dual review with at most two scoped fix/re-judgment rounds.
Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.
Trigger: /skill-creation, skill creation, skill creator, create skill, new skill. Create LLM-first skills with valid frontmatter.
Trigger: improve skills, audit skills, refactor skills, skill quality. Audit and upgrade existing LLM-first skills.
Trigger: update skills, skill registry, actualizar skills, after skill changes. Index available skills by trigger and path.
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
AI-generated documentation for GitHub repositories
Creates and removes isolated Git worktrees under a consistent repository sibling directory. Use when starting feature or fix work in a dedicated worktree, or cleaning up a finished worktree.
A JupyterLab extension supporting Claude Code, Copilot, Ollama, and OpenAI-compatible LLMs, with MCP, skills, plugins, and notebook agents.
Use when adding A2UI rendering to any AG-UI-supported framework or custom AG-UI application, scaffolding an AG-UI app that should render A2UI, adapting an AG-UI integration to emit A2UI surfaces, or wiring the AG-UI A2UI middleware/toolkit with a compatible renderer.
Core agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a websit
Control Herdr, a terminal multiplexer for coding agents. Use only when the user explicitly mentions Herdr or asks to use Herdr to inspect or control panes, tabs, workspaces, commands, or another agent. Do not use merely because a task could benefit from a background terminal, del
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.
/create-database-migrations
Create database migrations
Create and manage database migrations
/create-docs
Create docs
Analyze GitHub issue and create technical specification with implementation plan
/create-feature
Create feature
Scaffold new feature with boilerplate code
/create-jtbd
Create jtbd
Create a Jobs to be Done (JTBD) document for a product feature focusing on user needs
/create-onboarding-guide
Create onboarding guide
Create developer onboarding guide
/create-pr
Create pr
Create a new branch, commit changes, and submit a pull request with automatic commit splitting
/create-prd
Create prd
Create a Product Requirements Document (PRD) for a product feature
/create-prp
Create prp
Create a comprehensive Product Requirement Prompt (PRP) with research and context gathering
/create-pull-request
Create pull request
Guide for creating pull requests using GitHub CLI with proper templates and conventions
/create-worktrees
Create worktrees
Manage git worktrees for open PRs and create new branch worktrees
/cross-reference-manager
Cross reference manager
Manage cross-platform reference links
/debug-error
Debug error
Systematically debug and fix errors
/decision-quality-analyzer
Decision quality analyzer
Analyze decision quality with scenario testing, bias detection, and team decision-making process optimization.
/decision-tree-explorer
Decision tree explorer
Explore decision branches with probability weighting, expected value analysis, and scenario-based optimization.
/dependency-audit
Dependency audit
Audit dependencies for security vulnerabilities
/dependency-mapper
Dependency mapper
Map and analyze project dependencies
/design-database-schema
Design database schema
Design optimized database schemas
/design-rest-api
Design rest api
Design RESTful API architecture
/digital-twin-creator
Digital twin creator
Create systematic digital twins with data quality validation and real-world calibration loops.
/directory-deep-dive
Directory deep dive
Analyze directory structure and purpose
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0 views 0 likesProduction-ready open source terminal coding agent with readable, layered code: permission rules, OS sandboxing, MCP, skills, sub-agents, and Anthropic, OpenAI-…
0 views 0 likesAnswer me with HTML — an agent skill that answers hard questions with a one-page HTML you can actually read. 让 AI Agent 用一页 HTML 回答复杂问题。
1 views 0 likesPrompt packs that make any AI agent a LaTeX expert — fix errors, polish writing, format for venues, read papers, recover source
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