LLM Mart Basic
@llm-mart · Joined Jun 2026
Agent for Oracle-to-PostgreSQL application migrations. Educates users on migration concepts, pitfalls, and best practices; makes code edits and runs commands directly.
Responds to PagerDuty incidents by analyzing incident context, identifying recent code changes, and suggesting fixes via GitHub PRs.
Expert assistant for PHP MCP server development using the official PHP SDK with attribute-based discovery
Expert Pimcore development assistant specializing in CMS, DAM, PIM, and E-Commerce solutions with Symfony integration
Strategic planning and architecture assistant focused on thoughtful analysis before implementation. Helps developers understand codebases, clarify requirements, and develop comprehensive implementation strategies.
Generate an implementation plan for new features or refactoring existing code.
SRE-focused Kubernetes specialist prioritizing reliability, safe rollouts/rollbacks, security defaults, and operational verification for production-grade deployments
Testing mode for Playwright tests
Work with PostgreSQL databases using the PostgreSQL extension.
Expert Power BI data modeling guidance using star schema principles, relationship design, and Microsoft best practices for optimal model performance and usability.
Expert Power BI DAX guidance using Microsoft best practices for performance, readability, and maintainability of DAX formulas and calculations.
Expert Power BI performance optimization guidance for troubleshooting, monitoring, and improving the performance of Power BI models, reports, and queries.
Expert Power BI report design and visualization guidance using Microsoft best practices for creating effective, performant, and user-friendly reports and dashboards.
Power Platform expert providing guidance on Code Apps, canvas apps, Dataverse, connectors, and Power Platform best practices
Expert in Power Platform custom connector development with MCP integration for Copilot Studio - comprehensive knowledge of schemas, protocols, and integration patterns
Provide principal-level software engineering guidance with focus on engineering excellence, technical leadership, and pragmatic implementation.
Use Labtasker v2 to queue and run independent ML inference, evaluation, or experiment Tasks; migrate pipelines; design routes and Workers; inspect Task demand and Worker activity; and recover Tasks. Do not use it as a GPU allocator, cluster scheduler, workflow DAG, or artifact st
Write or revise Labtasker's README and user documentation, especially product positioning, tutorials, guides, examples, case studies, and navigation. Preserve the project's direct, plain-English style for ML researchers, agent-friendly workflow, and contract accuracy. Do not use
Change Labtasker's public Task lifecycle, HTTP API, Python API, CLI, configuration, query language, or persisted schema while keeping every public surface and invariant aligned. Do not use for internal refactors with no observable behavior change.
Prepare, validate, tag, or publish a Labtasker release. Use for version bumps, release readiness, release artifacts, tags, GitHub releases, or PyPI publication; do not use for ordinary development builds.
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.
/plugin-review
plugin-review
"Tiered plugin quality review: branch (quick gates),
/promote-discussions
promote-discussions
Check GitHub Discussions for highly voted learnings and promote them to Issues.
/rules-eval
rules-eval
Evaluate Claude Code rules in .claude/rules/ directories for quality
/skills-eval
skills-eval
Audit skill quality, frontmatter compliance, token efficiency, and activation reliability. Recommends improvements.
/test-skill
test-skill
Test Claude Code skills using RED/GREEN/REFACTOR TDD phases in fresh subagents to prevent priming bias.
/validate-hook
validate-hook
Validate hooks for security, performance, and SDK compliance
/validate-plugin
validate-plugin
Validate plugin structure, schema, and naming. Use for plugin creation, debugging, or verification.
/arch-init
arch-init
Initialize projects with architecture-aware templates using paradigm research and selection guidance for the target domain.
/blueprint
blueprint
Generate an implementation plan with system architecture design and dependency-ordered task breakdown from a specification.
/brainstorm
brainstorm
Guide project ideation through Socratic questioning to generate briefs with validated approaches and decision rationale.
/execute
execute
Execute implementation plan systematically with progress tracking and checkpoint validation
/mission
mission
Run full attune lifecycle as a mission with state detection and phase routing
/project-init
project-init
Initialize a new project with git setup, CI/CD workflows, pre-commit hooks, Makefiles, and language-specific tooling.
/skill-library
skill-library
Build a project skill library under .claude/skills/ as a resumable mission: discover, author in parallel, review adversarially.
/specify
specify
Create specs from project briefs with acceptance criteria and testable requirements
/upgrade-project
upgrade-project
Update existing project configurations to current best practices with selective component upgrades
/validate
validate
Validate project structure and configurations against best practices with detailed issue reporting
/war-room
war-room
Convene a multi-LLM expert panel to pressure-test strategic decisions with adversarial review and reversibility assessment.
/visualize
visualize
Generate visual diagrams of codebase structure using Mermaid Chart MCP rendering.
/ai-hygiene-audit
ai-hygiene-audit
Audit codebase for AI-generated code quality issues (vibe coding, Tab bloat, slop)
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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